System and method for identification of inappropriate multimedia content

Abstract

A system and method for identification of inappropriate multimedia content elements are provided. The method includes receiving a request to identify a multimedia content element from a user device; generating at least one signature respective of the received multimedia content element; matching between the at least one of generated signature respective of the multimedia content element and at least one signature of each concept designated as inappropriate; determining whether a match is identified between the at least one of signature generated respective of the multimedia content element and the at least one signature of an inappropriate concept; and preventing the display on a user device of the multimedia content element, upon identification of a match.

Description

All of the applications referenced above are herein incorporated by reference for all that they contain.

TECHNICAL FIELD

The present invention relates generally to the analysis of multimedia content, and more specifically to a system for identifying inappropriate elements in the multimedia content.

BACKGROUND

Due to the abundance of multimedia content made available through various means and, in particular, through the Internet, there is a need to provide effective filters in order to prevent the exposure of inappropriate content to users. The definition of inappropriate content is subjective and depends on the perspective of each person who may view such content. The differences among definitions of “inappropriate” are usually derived from a person's characteristics such as age, geographic location, religion, background, and the like. In some cases, a person or his or her supervisor may wish to control the content made available to such person.

A user or supervisor of that user may want to prevent the user from being exposed to certain portions of content. In such cases, the user and/or supervisor may desire to prevent display of such portions of content in multimedia content. As an example, a doctor may seek to prevent a pedophile from being exposed to images containing content related to infants as part of a medical treatment. As another example, a smoker who is currently undergoing rehabilitation may not want to be exposed to images containing content related to cigarettes and people smoking. As yet another example, a parent may wish to prevent his or her child from accessing content featuring excessively violent imagery and/or written or spoken foul language. Despite these needs to prevent the display of certain elements in multimedia content, such elements are still widely accessible and may be encountered in a variety of situations.

Prior art solutions for preventing exposure to certain content which are commonly used by search engines include methods for searching and identifying inappropriate sources of content such as, for example porn websites, and preventing the display of content received from such sources. The existing solutions typically filter inappropriate content based on, for example, URLs of websites tagged as inappropriate, content classification using textual and attributes analysis of the web-pages, and so on. Content retrieved from sources other than web-pages are typically scanned for viruses but not for the nature of the content.

Current solutions for content filtering are typically inefficient in cases where inappropriate content is received from a source which is not classified as inappropriate by the search engine. Furthermore, as the content available in the Internet continues to grow exponentially, the task of identifying every inappropriate source of inappropriate content has become increasingly difficult.

It would therefore be advantageous to provide a solution that would overcome the deficiencies of the prior art by providing an efficient and dynamic tool for preventing users from being exposed to inappropriate content.

SUMMARY

Certain embodiments disclosed herein include a method and system. The method includes a method for identification of inappropriate multimedia content elements. The method comprises receiving a request to identify a multimedia content element from a user device; generating at least one signature respective of the received multimedia content element; matching between the at least one of generated signature respective of the multimedia content element and at least one signature of each concept designated as inappropriate; determining whether a match is identified between the at least one of signature generated respective of the multimedia content element and the at least one signature of an inappropriate concept; and preventing the display on a user device of the multimedia content element, upon identification of a match.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter disclosed herein is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other objects, features, and advantages of the disclosed embodiments will be apparent from the following detailed description taken in conjunction with the accompanying drawings.

FIG. 1 is a schematic block diagram of a system utilized to describe the various embodiments for identifying inappropriate multimedia content elements;

FIG. 2 is a flowchart illustrating a method for preventing exposure of a user to inappropriate multimedia elements according to an embodiment;

FIG. 3 is a block diagram depicting the basic flow of information in a signature generator system;

FIG. 4 is a diagram illustrating the flow of patches generation, response vector generation, and signature generation in a large-scale speech-to-text system; and

FIG. 5 is a flowchart illustrating a method for determining the context indicated by the relationship between multimedia elements according to an embodiment.

DETAILED DESCRIPTION

It is important to note that the embodiments disclosed herein are only examples of the many advantageous uses of the innovative teachings herein. In general, statements made in the specification of the present application do not necessarily limit any of the various claimed embodiments. Moreover, some statements may apply to some inventive features but not to others. In general, unless otherwise indicated, singular elements may be in plural and vice versa with no loss of generality. In the drawings, like numerals refer to like parts through several views.

Certain exemplary embodiments disclosed herein include a system and method for identifying inappropriate elements within multimedia content. According to one embodiment, inappropriate multimedia elements may be determined based on a user's characteristics and/or a user's preferences. According to another embodiment, one or more preferences may be preconfigured by a user's supervisor. According to the embodiments disclosed herein, identification of a multimedia element or portion thereof as inappropriate is based on signatures matching. In an exemplary embodiment, the matching is between at least one signature generated for a received multimedia element and at least one signature of a concept determined as inappropriate. According to one embodiment, when a match is identified, a display of the inappropriate element may be prevented.

FIG. 1 shows an exemplary and non-limiting schematic diagram of a system 100 for identifying inappropriate multimedia content elements according to one embodiment. A network 110 is used to communicate between different parts of the system 100. The network 110 may be the Internet, the world-wide-web (WWW), a local area network (LAN), a wide area network (WAN), a metro area network (MAN), and other networks capable of enabling communication between the elements of the system 100.

Further connected to the network 110 are one or more client applications, such as web browsers (WB) 120-1 through 120-n (collectively referred to hereinafter as web browsers 120 or individually as a web browser 120, merely for simplicity purposes). A web browser 120 may be executed over a computing device of a user or over a computing device of a user's supervisor. In certain embodiments, the web browser 120 may be a mobile application (‘app’), a plug-in, an ad-on, and the like. The computing device may be, but is not limited to, a personal computer (PC), a personal digital assistant (PDA), a mobile phone, a smart phone, a tablet computer, a wearable computing device, and other kinds of wired and mobile appliances, equipped with browsing, viewing, listening, filtering, and managing capabilities etc., that are enabled as further discussed herein below.

A server 130 is further connected to the network 110. The server 130 may provide web-pages containing multimedia content, or references therein, to a web browser 120 upon request. The system 100 also includes a signature generator system (SGS) 140. In one embodiment, the SGS 140 is connected to the server 130. In another embodiment, the SGS 140 is implemented in the server 130. In yet another embodiment, the server 130 is configured to receive and serve multimedia content and causes the SGS 140 to generate a signature respective of the multimedia content.

It should be noted that each of the server 130 and the SGS 140 typically includes a processing unit such as a processor (not shown) that is coupled to a memory. The memory typically contains instructions that can be executed by the processor.

A plurality of web sources 150-1 through 150-m are also connected to the network 110, each of which is a source for multimedia content. For example, a web source 150-1 may be a web server hosting web pages, a web source 150-2 may be a server hosting mobile application, a web source 150-m may be a repository for medical records, and the like. The web sources 150-1 through 150-m are accessible to the server 130 through the network 110. A data storage unit, such as a data warehouse 160, may be utilized at least for maintaining inappropriate concepts together with at least one signature respective thereto.

A concept is a collection of signatures representing multimedia elements of the unstructured data and metadata describing the concept. As a non-limiting example, a ‘Superman concept’ is a signature reduced cluster of signatures describing elements (such as multimedia elements) related to, e.g., a Superman cartoon: a set of metadata representing textual representation of the Superman concept. Therefore, the concept can provide a unique identification of the multimedia content input. A concept is an abstract description of the content to which the signature was generated. For example, a concept of the signature generated for a picture showing a bouquet of red roses is “flowers.” A cluster reduction process for generating a signature reduced cluster is performed. Specifically, the purpose of the operation is to ensure that in the cluster there remains the minimal number of signatures that still identify all of the MMDEs that are associated with the signature reduced cluster (SRC). This can be performed, for example, by attempting to match the signatures of each of the MMIDEs associated with the SRC having one or more signatures removed there from. In one embodiment of the invention the process of cluster reduction for the purpose of generating SRCs is performed in parallel and independently of the process described herein above.

With respect to clustered signatures related to multimedia elements, a concept is a match that is common among one or more multimedia elements. Concept generation and identification is discussed in more detail in the U.S. Pat. No. 8,266,185, assigned to common assignee, which is hereby incorporated by reference for all that it contains.

Inappropriate concepts are concepts that relate to subject matter that may be inappropriate in certain situations determined by a user and/or supervisor. As a non-limiting example, with respect to a smoker who recently quit smoking, inappropriate concepts may include, but are not limited to, cigarettes, people smoking, and the like. As another non-limiting example, a parent (i.e. a supervisor) of a child may find foul language, violence, and nudity inappropriate for his or her child. In such a case, inappropriate concepts may include, but are not limited to, curse words, weapons, blood, and modest body parts.

Concepts may be identified as inappropriate when, e.g., a signature of the concept matches signatures of one or more inappropriate concepts. As a non-limiting example for a smoker who recently quit smoking, portions of an image illustrating a pack of cigarettes may be inappropriate content found within the multimedia content.

The data warehouse 160 is typically connected to the server 130 either directly or through the network 110. In some embodiments, the at least one inappropriate concept may be received or retrieved from a user, another data source, and so on.

According to the embodiments disclosed herein, a multimedia element is received by the server 130. The multimedia element can be generated and sent by a script executed in a web-page, an agent installed in the web-browser, or by one of the web sources 150. The request to analyze the multimedia element may include a URL of the web-page or a copy of the web-page. Moreover, the multimedia element may be extracted from the web-page. A multimedia element may be, but is not limited to, an image, a graphic, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, and an image of signals (e.g., spectrograms, phasograms, scalograms, etc.), and/or combinations thereof and portions thereof.

The server 130 is configured to analyze the multimedia content to identify the multimedia elements shown in it. Then, the server 130 is configured to generate by the SGS 140 at least one signature for each multimedia element. The generated signature(s) may be robust to noise and distribution as discussed below. Each signature represents a concept to be tested in order to identify whether it is an appropriate concept. In an embodiment, the tested concept may be identified as inappropriate if its signature matches the signature(s) of one or more predetermined inappropriate concepts. A concept may be predetermined to be inappropriate when, e.g., the concept is designated by a user or supervisor as inappropriate. In another embodiment, the concept may be determined as inappropriate based on a user's characteristics received from a user or a supervisor. As noted herein, each concept has a signature representing the concept.

In an embodiment, the server 130 is further configured to correlate the generated signature(s) to the at least one signature of a predetermined inappropriate concept. The correlation between concepts can be achieved by identifying a ratio between signatures' sizes, a spatial location of each signature, and so on using probabilistic models. A strong match is determined when there are more concepts, or when the each concept of the plurality of concepts satisfies the same predefined condition as other concepts of the plurality of concepts.

As a non-limiting example, a curse word may be pre-determined by a supervisor as an inappropriate concept. The signature(s) associated with the curse word may be stored, e.g., in the data warehouse 160. A multimedia content is received containing various words. Signature(s) may be generated for each word. The signatures of the words are each compared to the signature(s) of the predetermined inappropriate concept. In this example, one of the signatures generated for the words contained in the multimedia content matches the signature(s) of the predetermined inappropriate concept. Thus, the word associated with that signature(s) may be identified as related to an inappropriate concept.

Each inappropriate concept may be retrieved with its respective one or more signatures from the data warehouse 160, from the web browser 120, from the user's supervisor device, and so on. According to one embodiment, the server 130 is configured to generate at least one signature respective of each inappropriate concept received by the SGS 140. In a further embodiment, retrieval of such signature(s) respective of an inappropriate concept may be unnecessary.

In one embodiment, upon identification of at least one match between the inappropriate concept and the concept needed to be tested, the server 130 is configured to block the concept that is found to be inappropriate and/or the multimedia content element thereof. It should be noted that blocking the inappropriate concept may involve, but is not limited to, removing the inappropriate concept, occluding the inappropriate concept, making the inappropriate concept blurred and so on.

FIG. 2 depicts an exemplary and non-limiting flowchart 200 illustrating a method of identifying an inappropriate concept within a multimedia content element according to one embodiment. Inappropriate concepts are discussed further herein above with respect to FIG. 1. In S210, a multimedia element is received. Such a multimedia element may be, but is not limited to, an image, graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, images of signals, combinations thereof, and portions thereof. The multimedia element may be received from a script running on an uploaded web-page, a web-browser (e.g., web-browser 120), and the like. S210 may also involve extraction of the multimedia element from the web-page and identification of one or more multimedia elements shown therein.

In S220, at least one signature is generated respective of the multimedia content element or portion thereof. Signature generation is described further herein below with respect to FIGS. 3 and 4. Each signature represents a concept to be tested. A concept is an abstract description of a multimedia content element to which at least one signature is generated. As an example, a concept of the signature generated for a picture showing a bouquet of red roses is “flowers.” As another example, a concept of a bouquet of wilted roses is “wilted flowers.” Concept generation and identification is discussed in more detail in U.S. Pat. No. 8,266,185 referenced above.

In S230, at least one predetermined inappropriate concept is retrieved together with at least one signature. The predetermined inappropriate concept may be, but is not limited to, body parts, text content, objects, symbols, locations, and so on. In various embodiments, the predetermined inappropriate concept and/or its signature(s) may be received from a user via a user device (e.g., the web browser 120), from a user's supervisor via a supervisor user device (not shown), and so on. In various other embodiments, the signature respective of the predetermined inappropriate concept may not be retrieved. Rather, in such embodiments, the predetermined inappropriate concept alone (without any signature) may be retrieved. Each concept includes at least one signature representing the concept regardless of whether the concept is appropriate or inappropriate.

According to an embodiment, an inappropriate concept may be adjusted based on a user's characteristics. The user's characteristics may be, but are not limited to, age, geographic location, religion, background, and so on.

According to another embodiment, one or more inappropriate concepts may be received as an input from a user device (e.g., web browser 120) or, alternatively, may be received as an input from a user's supervisor's device. The user's supervisor may be an authority which desires to prevent display of inappropriate concepts to the user. A supervisor may be, but is not limited to, a parent, a guardian, an employer, a manager, and the like.

It should be understood that each inappropriate concept is retrieved, received or predetermined respective of the user's characteristics. Then, each inappropriate concept is analyzed, and at least one signature is generated respective thereto. The signatures together with the inappropriate concept may be stored for further use.

In S240, the at least one signature generated respective of the multimedia content is correlated to at least one signature that represents a predetermined inappropriate concept to determine whether a match is found respective thereof. The correlation or other matching between a multimedia element and an inappropriate concept can be achieved by identifying a ratio between signatures' sizes, a spatial location of each signature, and so on using probabilistic models. A strong match may be determined, for example, when there are more concepts, or when each concept of the plurality of concepts satisfies the same predefined condition as each other concept of the plurality of concepts.

In S250, it is checked whether a match is found and, if so, execution continues with S260; otherwise, execution terminates. In S260, at least one multimedia element identified as inappropriate is blocked. Blocking may include, but is not limited to, removal of the identified inappropriate concept, occluding the identified inappropriate concept, or blurring of the identified inappropriate concept. In S270, it is checked whether additional multimedia content have been received and, if so, execution continues with S210; otherwise, execution terminates.

As a non-limiting example, a multimedia content element that is a video clip of the singer “Madonna” is received and signatures are generated respective thereto. The signatures may be generated for example, for the “cone bra”, “blond hair”, “crucifix”, “audience”, “stage”, “dancers”, and so on. According to this example, the user who desires to view the video clip is a 6 year-old boy from. Consequently, several signatures of predetermined inappropriate concepts adjusted to the user characteristics are retrieved from a database (e.g., data warehouse 160) including the predetermined inappropriate concepts of “bra” and of “crucifix.”

The signatures generated for the video clip are correlated with the signatures associated with each predetermined inappropriate concepts. A match is found with the predetermined inappropriate concept of “bra” with respect to the cone bra which appears in the video clip and the inappropriate concept of “crucifix” with respect to the crucifix which appears in the video clip. In accordance with the embodiments disclosed herein, probabilistic models may be used to identify that the signatures' sizes of “bra” is similar to “cone bra.” Moreover, a spatial location of the signature of “cone bra” is found on Madonna and it covers her upper body, when the “bra” is worn by Madonna, thereby signaling a match to the predetermined inappropriate concept. Upon matching signatures in the video to signatures of predetermined inappropriate concepts, the “crucifix” and the “cone bra” found in the video clip are blocked via blurring.

According to one embodiment, the context of the multimedia content element may be determined. A context is determined by analyzing the multimedia elements shown in the multimedia content. Context determination is described further herein below with respect to FIG. 5. Based on this determination, it is determined whether the context of the multimedia content is inappropriate. Moreover, a notification may be sent to the user's supervisor if the context of the multimedia content is found to be inappropriate.

FIGS. 3 and 4 illustrate the generation of signatures for the multimedia content elements by the SGS 140 according to one embodiment. An exemplary high-level description of the process for large scale matching is depicted in FIG. 3. In this example, the matching is for a video content.

Video content segments 2 from a Master database (DB) 6 and a Target DB 1 are processed in parallel by a large number of independent computational Cores 3 that constitute an architecture for generating the Signatures (hereinafter the “Architecture”). Further details on the computational Cores generation are provided below. The independent Cores 3 generate a database of Robust Signatures and Signatures 4 for Target content-segments 5 and a database of Robust Signatures and Signatures 7 for Master content-segments 8. An exemplary and non-limiting process of signature generation for an audio component is shown in detail in FIG. 4. Finally, Target Robust Signatures and/or Signatures are effectively matched, by a matching algorithm 9, to Master Robust Signatures and/or Signatures database to find all matches between the two databases.

The Signatures' generation process will now be described with reference to FIG. 4. The first step in the process of signatures generation from a given speech-segment is to breakdown the speech-segment to K patches 14 of random length P and random position within the speech segment 12. The breakdown is performed by the patch generator component 21. The value of the number of patches K, random length P and random position parameters is determined based on optimization, considering the tradeoff between accuracy rate and the number of fast matches required in the flow process of the server 130 and SGS 140. Thereafter, all the K patches are injected in parallel into all computational Cores 3 to generate K response vectors 22, which are fed into a signature generator system 23 to produce a database of Robust Signatures and Signatures 4.

In order to generate Robust Signatures, i.e., Signatures that are robust to additive noise L (where L is an integer equal to or greater than 1) by the Computational Cores 3 a frame ‘i’ is injected into all the Cores 3. Then, Cores 3 generate two binary response vectors: {right arrow over (S)} which is a Signature vector, and {right arrow over (RS)} which is a Robust Signature vector.

For generation of signatures robust to additive noise, such as White-Gaussian-Noise, scratch, etc., but not robust to distortions, such as crop, shift and rotation, etc., a core C_i={n_i} (1≤i≤L) may consist of a single leaky integrate-to-threshold unit (LTU) node or more nodes. The node n_i equations are:

$\begin{array}{cc}{V}_i=\sum _j{w}_{\mathrm{ij}}{k}_j& n_i=\Theta \left(\mathrm{Vi}-{\mathrm{Th}}_x\right)\end{array}$

where, Θ is a Heaviside step function; w_ij is a coupling node unit (CNU) between node i and image component j (for example, grayscale value of a certain pixel j); k_j is an image component ‘j’ (for example, grayscale value of a certain pixel j); Thx is a constant Threshold value, where x is ‘S’ for Signature and ‘RS’ for Robust Signature; and Vi is a Coupling Node Value.

The Threshold values Thx are set differently for Signature generation and for Robust

Signature generation. For example, for a certain distribution of Vi values (for the set of nodes), the thresholds for Signature (ThS) and Robust Signature (Th_RS) are set apart, after optimization, according to at least one or more of the following criteria:

• • 1: For: V_i>Th_RS 1−p(V>Th_s)−1−(1−∈)^l «1

i.e., given that nodes (cores) constitute a Robust Signature of a certain image I, the probability that not all of these I nodes will belong to the Signature of same, but noisy image, Ĩ is sufficiently low (according to a system's specified accuracy).

• • 2: p(V_i>Th_RS)≈l/L i.e., approximately l out of the total L nodes can be found to generate a Robust Signature according to the above definition.
  • 3: Both Robust Signature and Signature are generated for certain frame i.

It should be understood that the generation of a signature is unidirectional, and typically yields lossless compression, where the characteristics of the compressed data are maintained but the uncompressed data cannot be reconstructed. Therefore, a signature can be used for the purpose of comparison to another signature without the need of comparison to the original data. Detailed description of the Signature generation is discussed in more detail in the co-pending patent applications of which this patent application is a continuation-in-part, which are hereby incorporated by reference.

A Computational Core generation is a process of definition, selection, and tuning of the parameters of the cores for a certain realization in a specific system and application. The process is based on several design considerations, such as:

(a) The Cores should be designed so as to obtain maximal independence, i.e., the projection from a signal space should generate a maximal pair-wise distance between any two cores' projections into a high-dimensional space.

(b) The Cores should be optimally designed for the type of signals, i.e., the

Cores should be maximally sensitive to the spatio-temporal structure of the injected signal, for example, and in particular, sensitive to local correlations in time and space. Thus, in some cases a core represents a dynamic system, such as in state space, phase space, edge of chaos, etc., which is uniquely used herein to exploit their maximal computational power.

(c) The Cores should be optimally designed with regard to invariance to a set of signal distortions, of interest in relevant applications.

Detailed description of the Computational Core generation and the process for configuring such cores is discussed in more detail in the above-referenced U.S. Pat. No. 8,655,801, assigned to the common assignee, which is hereby incorporated by reference for all that it contains.

FIG. 5 is a flowchart 500 illustrating determination of a context of a multimedia content element retrieved from a web-page. In S510, the method starts when a web-page is uploaded to a web-browser (e.g., web-browser 120-1). In another embodiment, the method starts when a web server (e.g., web-browser 150-1) receives a request to host the requested web-page.

In S520, a uniform resource locator (URL) of the web-page to be processed is received. In an embodiment, the uploaded web-page includes an embedded script. In that embodiment, the script extracts the URL of the web-page and may send the URL to a server (e.g., the server 130). In another embodiment, an add-on installed in a web-browser (e.g., the web browser 120) may extract the URL of the uploaded web-page and send the URL to a server. In yet another embodiment, an agent may be installed on a user device (e.g., user device 120) executing a web browser. The agent is configured to monitor web-pages uploaded to the web-site, extract the URLs, and send them to the server. In another embodiment, the web-server (e.g., an information source 150-1) hosting the requested web-page provides the server with the URL of the requested web-page. It should be noted that only URLs of selected web sites can be sent to the server such as, for example, URLs related to web-sites that paid for the additional information.

In S530, the web-page respective of each received URL is downloaded. In S540, each downloaded web-page is analyzed in order to identify the existence of one or more multimedia elements in the uploaded web-page. Each identified multimedia element is extracted from the web-page and, in an embodiment, may be sent to a SGS (e.g., the SGS 140). In S550, at least one signature is generated for each identified multimedia element. The at least one signature is robust for noise and distortion. The signatures for the multimedia elements are generated as described in greater detail herein above with respect to FIGS. 3 and 4.

In S560, the correlation between the signatures of all extracted multimedia elements and between any identified inappropriate concepts is determined. It should be noted that each signature represents a different concept. The signatures are analyzed to determine the correlation between concepts. A concept is an abstract description of the content to which the signature was generated. For example, a concept of the signature generated for a picture showing a bouquet of red roses is “flowers”. The correlation between concepts can be achieved by identifying a ratio between signatures' sizes, a spatial location of each signature, and so on using probabilistic models. As noted above, a signature represents a concept and is generated for a multimedia element. Thus, identifying, for example, the ratio of signatures' sizes may also indicate the ratio between the sizes of their respective multimedia elements.

A context is determined as the correlation between the concepts. A strong context may be determined when there are multiple correlation matches among concepts, or when each concept of a plurality of concepts satisfies the same predefined condition. As an example, the server (each server 130) is configured to analyze signatures generated for multimedia elements of a smiling child with a Ferris wheel in the background. The concept of the signature of the smiling child is “amusement” and the concept of a signature of the Ferris wheel is “amusement park”. The server 130 further analyzes the relation between the signatures of the child and recognized wheel, to determine that the Ferris wheel is bigger than the child. The relation analysis determines that the Ferris wheel is used to entertain the child. Therefore, the determined context may be “amusement.”

According to one embodiment, one or more typical probabilistic models may be used to determine the correlation between signatures representing concepts. The probabilistic models may determine, for example, the probability that a signature may appear in the same orientation and in the same ratio as another signature. When performing the analysis, information maintained in a database (e.g., the data warehouse 160) may be utilized such as, for example, signatures previously analyzed. In such embodiments, a match may be determined if, for example, two signatures appear in the same orientation when the probability of such orientation is low (e.g., 10%, 1%, 0.1%, etc.).

In S570, based on the analysis performed in S560, the context of a plurality of multimedia elements that exist in the multimedia content and in the context of the web-page is determined. If there is a strong correlation between multimedia elements in the web-page and one or more predetermined inappropriate concepts, the context of the multimedia content showing strong correlations may be “inappropriate.” In S580, the context of the multimedia content together with the respective signatures is stored for future use.

In an embodiment, S580 may further include, upon determining that the context of the multimedia element is “inappropriate,” identifying that the web-page features inappropriate content. In further embodiments, such inappropriate content may be blocked to that user and/or may be flagged as inappropriate for other users. Flagging a web-page as inappropriate may involve, but is not limited to, generating and sending a message to one or more search engines. This may allow other users to be warned of the web-page's content and/or to filter content on the web-page prior to viewing or listening to content on the web-page. In S590, it is checked whether there are additional web-pages to be analyzed and, if so, execution continues with S510; otherwise, execution terminates.

As a non-limiting example, an image that contains a plurality of multimedia elements is identified in an uploaded web-page. At least one signature is generated for each of the plurality of multimedia elements that exist in the image. According to this example, multimedia contents featuring the singer “Adele”, the “red carpet,” and a “Grammy” award are shown in the image. Signatures are generated respective thereto. The correlation between “Adele”, “red carpet,” and the “Grammy” award is analyzed, and the context of the image is determined based on the correlation. According to this example, such a context may be “Adele Wining the Grammy Award”.

As another non-limiting example, a web page containing a plurality of multimedia elements is identified in an uploaded web-page. According to this example, signatures are generated for objects such as a “glass,” a “cutlery,” and a “plate” which appear in the multimedia elements. The correlation between the concepts generated by signatures respective of the data is then analyzed based on, for example, analysis of previously generated signatures. According to this example, since all of the concepts of “glass,” “cutlery,” and “plate” satisfy the same predefined condition (e.g., items commonly found on a table set), a strong context is determined. The context of such concepts may be determined to be a “table set.” The context can also be determined respective of a ratio of the sizes of the objects (glass, cutlery, and plate) in the image and the distinction of their spatial orientation. For example, if the plate is determined to be slightly larger than the glass and the cutlery, and all of the items are placed close to each other within an image, the context may be determined to be a “table set.” In contrast, if the cutlery is much larger than the plate and the items are all far apart within the image, the context may be determined to not be a “table set.”

As yet another non-limiting example, a user seeks to visit a web-page featuring content related to the video game “Grand Theft Auto.” In this example, the user is a 10-year-old child. The web-page is uploaded to a web browser and the URL of the uploaded web-page is received. The web-page associated with the URL is downloaded. The web-page features multimedia content showing, among other multimedia elements, a gun being fired. Signatures are generated respective thereto.

In accordance with an embodiment, the signatures are analyzed and correlation to one or more signatures of inappropriate concepts retrieved from a database (e.g., data warehouse 160). In this example, there is a strong correlation between the “gun being fired” element and the inappropriate concept “excessive violence” due to the presence of a gun and a bullet, the speed of the bullet exiting the gun, and the flash as the gun is fired. Consequently, the context of the multimedia content is determined as “excessive violence.” The context and its respective signature are stored. In accordance with an embodiment, the web-page is identified as containing inappropriate content. Consequently, multimedia contents featuring a gun being fired on the web-page may be blocked, or the user may be denied access to the web-page entirely. Additionally, a message indicating the site's inappropriate content may be generated and sent to, e.g., Google@, Yahoo®, Bing®, and so on.

The various embodiments disclosed herein can be implemented as hardware, firmware, software, or any combination thereof. Moreover, the software is preferably implemented as an application program tangibly embodied on a program storage unit or computer readable medium consisting of parts, or of certain devices and/or a combination of devices. The application program may be uploaded to, and executed by, a machine comprising any suitable architecture. Preferably, the machine is implemented on a computer platform having hardware such as one or more central processing units (“CPUs”), a memory, and input/output interfaces. The computer platform may also include an operating system and microinstruction code. The various processes and functions described herein may be either part of the microinstruction code or part of the application program, or any combination thereof, which may be executed by a CPU, whether or not such a computer or processor is explicitly shown. In addition, various other peripheral units may be connected to the computer platform such as an additional data storage unit and a printing unit. Furthermore, a non-transitory computer readable medium is any computer readable medium except for a transitory propagating signal.

All examples and conditional language recited herein are intended for pedagogical purposes to aid the reader in understanding the principles of the invention and the concepts contributed by the inventor to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure.

Claims

1. A method for identification of inappropriate multimedia content elements, comprising: receiving a request to identify a multimedia content element from a user device;generating at least one signature for the received multimedia content element;matching between the at least one generated signature for the received multimedia content element and at least one signature of each of at least one inappropriate concept, wherein each inappropriate concept is a concept that is designated as inappropriate, wherein each of the at least one inappropriate concept is associated with a plurality of multimedia content elements, and includes a reduced cluster of signatures representing the plurality of multimedia content elements, and textual metadata related to the plurality of multimedia content elements;determining whether a match is identified between the at least one signature generated for the received multimedia content element and the at least one signature of at least one inappropriate concept; andpreventing a display on a user device of the received multimedia content element, upon identification of a match.

2. The method of claim 1, wherein the at least one inappropriate concept is determined based on a set of characteristics of a user of the user device.

3. The method of claim 2, wherein the characteristics of the user of the user device are at least one of: age, geographic location, religion, and background.

4. The method of claim 1, wherein each inappropriate concept is any of: retrieved from a data warehouse with its respective at least one signature, received as an input from a user device, and received as an input from a user's supervisor's device.

5. The method of claim 1, wherein the signatures representing the plurality of multimedia content elements represent responses of one or more neural networks to the plurality of multimedia content elements.

6. The method of claim 1, further comprising: generating the reduced cluster of signatures by performing a cluster reduction process that comprises reducing a number of signatures of the reduced cluster while remaining a minimal number of signatures to that still identify all of the plurality of multimedia content items.

7. The method of claim 1 comprising generating the at least one signature for received multimedia content by a plurality of at least partially statistically independent computational cores.

8. The method of claim 1, further comprising: using at least one probabilistic model to determine whether the match is identified.

9. A non-transitory computer readable medium having stored thereon instructions for causing at least one processing unit to execute a method for identification of inappropriate multimedia content elements, comprising: receiving a request to identify a multimedia content element from a user device; generating at least one signature for the received multimedia content element; matching between the at least one generated signature for the received multimedia content element and at least one signature of each of at least one inappropriate concept, wherein each inappropriate concept is a concept that is designated as inappropriate, wherein each of the at least one inappropriate concept is associated with a plurality of multimedia content elements, and includes a reduced cluster of signatures representing the plurality of multimedia content elements, and textual metadata related to the plurality of multimedia content elements; determining whether a match is identified between the at least one signature generated for the received multimedia content element and the at least one signature of at least one inappropriate concept; and preventing a display on a user device of the received multimedia content element, upon identification of a match.

10. A system for removal of an inappropriate concept, comprising: a network interface configured to receive a request to identify a multimedia content element from a user device; a processor; a memory communicatively connected to the processor, wherein the memory contains instructions that, when executed by the processor, configure the system to: generate at least one signature for the received multimedia content element; match between the at least one generated signature for the received multimedia content element and at least one signature of each of at least one inappropriate concept, wherein each inappropriate concept is a concept that is designated as inappropriate, wherein each of the at least one inappropriate concept ef is associated with a plurality of multimedia content elements, and includes a reduced cluster of signatures representing the plurality of multimedia content elements, and textual metadata related to the plurality of multimedia content elements; determine whether a match is identified between the at least one signature generated for the received multimedia content element and the at least one signature of at least one inappropriate concept; and prevent a display on a user device of the received multimedia content element, upon identification of a match.

11. The system of claim 10, wherein the system is communicatively connected to a data warehouse for maintaining the at least one inappropriate concept with its respective at least one signature.

12. The system of claim 10, wherein each inappropriate concept is any of: retrieved from the data warehouse with its respective at least one signature, received as an input from a user device, and received as an input from the user's supervisor device.

13. The system of claim 12, wherein the at least one signature for the received multimedia content element is generated by a signature generator system (SGS), wherein the SGS is communicatively connected to the system.

14. The system of claim 11, wherein the system is further configured to: generate the reduced cluster of signatures by performing a cluster reduction process that comprises reducing a number of signatures of the reduced cluster while remaining a minimal number of signatures to that still identify all of the plurality of multimedia content items.

15. The system of claim 11, wherein the signatures representing the plurality of multimedia content elements represent responses of one or more neural networks to the plurality of multimedia content elements.

16. The system of claim 10, wherein the system is further configured to use at least one probabilistic model to match between the signatures.

17. The system of claim 10, wherein the received multimedia content element is at least one of: an image, graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, images of signals, and portions thereof.

18. The system of claim 10, wherein the at least one inappropriate concept is determined based on a set of characteristics of a user of the user device.

19. The system of claim 18, wherein the user's characteristics are at least one of: age, geographic location, religion, and background.

20. The method of claim 1, wherein each signature is generated by a signature generator system, wherein the signature generator system includes a plurality of computational cores configured to receive a plurality of unstructured data elements, each computational core of the plurality of computational cores having properties that are at least partly statistically independent of other of the computational cores, the properties are set independently of each other core.