Patent Application
20130262430
A large number of search queries can be name queries (queries looking for more information about a particular person). A problem with search results for people queries is that the results returned are frequently ambiguous. That is, results are returned for several different people with identical names making it difficult to disambiguate and know which results correspond to the particular person the user wants. This is especially true for queries related to non-famous people.
The following presents a simplified summary in order to provide a basic understanding of some novel embodiments described herein. This summary is not an extensive overview, and it is not intended to identify key/critical elements or to delineate the scope thereof. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
The disclosed architecture computes a dominant image from one or more images on a webpage. A dominant image classifier scans webpages in an offline-created index to identify the prominent images in the webpages. In a more specific implementation the image selected is the image associated with a name query. Face detection technology can be utilized to identify which of the images on a given webpage contain faces. A query classifier identifies queries that contain people names. In the context of search engines and search result pages, the web results for name queries can further include prominent people face images as thumbnail images.
Additional facts (structured data) can further be included that together with the results elements of caption title, snippet and attribute (uniform resource locator (URL)) provide an improved summary of the person on the page. Moreover, the image and structured data improve the user's ability to judge which results belong to which person, and therefore, aid in the role of “informing the click”. The structured data shown can depend on the website of the result and may vary from website to website.
To the accomplishment of the foregoing and related ends, certain illustrative aspects are described herein in connection with the following description and the annexed drawings. These aspects are indicative of the various ways in which the principles disclosed herein can be practiced and all aspects and equivalents thereof are intended to be within the scope of the claimed subject matter. Other advantages and novel features will become apparent from the following detailed description when considered in conjunction with the drawings.
The disclosed architecture computes a dominant image from one or more images on a webpage. A dominant image classifier scans webpages in an offline-created index to identify the prominent images in the webpages. In a more specific implementation the image selected is the image associated with a name query. Face detection technology can be utilized to identify which of the images on a given webpage contain faces. A query classifier identifies queries that contain people names. In the context of search engines and search result pages, the web results for name queries can further include prominent people face images as thumbnail images. Additional facts (structured data) can further be included that together with the results elements of caption title, snippet and attribute (uniform resource locator (URL)) provide an improved summary of the person on the page.
Examples of structured data include, but are not limited to, data from professional networking websites (e.g., job title, employer, occupation and location), data from social networking and community driven websites (e.g., number of tweets, number of followers, number following, number of questions, number of answers, etc.), and data from profession-specific online resources such as for doctors (e.g., specialty, years of experience, and patient rating, etc.).
People captions assist users by reducing the overall time it takes the user to find the page (or person) sought and improving perceived relevance of the search engine results page (SERP). In cases where the SERP does not present the appropriate results, at least a sufficient amount of information is presented for a successful re-query.
An image is shown in combination with a search result at least insofar where the query is a name query and the underlying webpage includes a prominent image that is a face. Face images (also referred to herein as person images and people images) in search results assist the user by reducing the overall time to perceive relevance of the SERP.
This differs from conventional approaches where an image may be shown with the search result if the webpage belongs to a pre-defined set of well-known websites and also has an image available at a pre-defined location on the page.
Generally, in operation, an image analysis component (e.g., a dominant image classifier) analyzes each webpage for the image metadata as part of an offline process and classifies an image of a webpage as the dominant image for that webpage. As an offline process, dominant images (also referred to a prominent images) within each webpage are computed (determined) in a web search engine index. A webpage may have one or more dominant images or have none. The offline process also uses face detection technology to identify and tag the dominant images within each webpage that contain a face.
Metadata about the dominant images in a webpage is added to each webpage in the index. When a user enters a name query into the search engine, a name query classifier determines if the query contains a person name. For each webpage returned by the search engine for the query, the systems checks to determine if one or more dominant face images are available for the page. If so, one of the face images (chosen by a heuristic such as the dominance score or the confidence in face detection) is chosen to be displayed in thumbnail form as part of the result for the webpage on the search engine results page.
Alternatively, or in combination therewith, when a user enters a query into the search engine, a query classifier computes if the query refers to a type of person and associated context (e.g., a query “actor in the movie Titanic” can also show an image of Leonardo DiCaprio as one of the actors, or additional actors can also be shown). For each webpage returned by the search engine for the query, the systems checks to determine if one or more dominant face images are available for the page. If so, one of the face images (chosen by a heuristic such as the dominance score or the confidence in face detection) is chosen to be displayed in thumbnail form as part of the result for the webpage on the search engine results page.
Reference is now made to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding thereof. It may be evident, however, that the novel embodiments can be practiced without these specific details. In other instances, well known structures and devices are shown in block diagram form in order to facilitate a description thereof. The intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the claimed subject matter.
Note that in this specific implementation, dominant image computation and determination is for purposes of query and search processing. However, it is to be understood that dominant image processing can be for the sole purpose of detecting which of multiple images on a webpage is to be considered a dominant image. In the example of
The dominant images can be (include) images of individual persons, for example, or any image as determined dominant for that associated webpage. The dominant images (e.g., image 118) can be presented as thumbnail images proximate the corresponding search results. The dominant image is a single image obtained from the associated webpage.
The system 100 can further comprise an image analysis component 122 that analyzes each webpage for image metadata (e.g., image metadata 110) as part of an offline process and classifies an image of a webpage as the dominant image for that webpage.
The system 100 can further comprise an indexing component 124 that creates an index 126 of the image metadata and an associated search result (related webpage data) as an offline process. The image analysis component 122 further analyzes each webpage for structured data that is presented with the corresponding dominant image and search result. At least one of the image or the structured data can be retrieved (or received) from the associated webpage or an off-page resource. The presentation component 112 further comprises an expansion component 128 that presents additional information proximate the corresponding result in response to a user action.
In this implementation, a first dominant person image 202 (e.g., the first dominant image 116 of
The system 200 can further comprise the image analysis component 122 that analyzes each webpage for person image metadata 210 (e.g., as part of the image metadata 110 of
The system 200 can further comprise the indexing component 124 that creates the index 126 of person image metadata and an associated search result (related webpage data) as an offline process. The image analysis component 122 can further analyze each target webpage for structured data that is presented with the corresponding dominant image and search result. At least one of the person image or the structured data can be retrieved (or received) from the associated webpage or an off-page resource. The presentation component 112 can further comprise the expansion component 128 that presents additional information proximate the corresponding result in response to a user action (e.g., hover, mouse-over, etc.).
Once the image metadata is obtained, at 506, flow is to 514, where a dominant face image is determined based on the image metadata. Where there are multiple images, additional heuristics can be employed, if necessary. At 516, the dominant image chosen can be rendered on the result page as a thumbnail image proximate the associated search result on the search engine results page (SERP) for each webpage.
Included herein is a set of flow charts representative of exemplary methodologies for performing novel aspects of the disclosed architecture. While, for purposes of simplicity of explanation, the one or more methodologies shown herein, for example, in the form of a flow chart or flow diagram, are shown and described as a series of acts, it is to be understood and appreciated that the methodologies are not limited by the order of acts, as some acts may, in accordance therewith, occur in a different order and/or concurrently with other acts from that shown and described herein. For example, those skilled in the art will understand and appreciate that a methodology could alternatively be represented as a series of interrelated states or events, such as in a state diagram. Moreover, not all acts illustrated in a methodology may be required for a novel implementation.
As used in this application, the terms “component” and “system” are intended to refer to a computer-related entity, either hardware, a combination of software and tangible hardware, software, or software in execution. For example, a component can be, but is not limited to, tangible components such as a processor, chip memory, mass storage devices (e.g., optical drives, solid state drives, and/or magnetic storage media drives), and computers, and software components such as a process running on a processor, an object, an executable, a data structure (stored in volatile or non-volatile storage media), a module, a thread of execution, and/or a program.
By way of illustration, both an application running on a server and the server can be a component. One or more components can reside within a process and/or thread of execution, and a component can be localized on one computer and/or distributed between two or more computers. The word “exemplary” may be used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs.
Referring now to
In order to provide additional context for various aspects thereof,
The computing system 1100 for implementing various aspects includes the computer 1102 having processing unit(s) 1104, a computer-readable storage such as a system memory 1106, and a system bus 1108. The processing unit(s) 1104 can be any of various commercially available processors such as single-processor, multi-processor, single-core units and multi-core units. Moreover, those skilled in the art will appreciate that the novel methods can be practiced with other computer system configurations, including minicomputers, mainframe computers, as well as personal computers (e.g., desktop, laptop, etc.), hand-held computing devices, microprocessor-based or programmable consumer electronics, and the like, each of which can be operatively coupled to one or more associated devices.
The system memory 1106 can include computer-readable storage (physical storage media) such as a volatile (VOL) memory 1110 (e.g., random access memory (RAM)) and non-volatile memory (NON-VOL) 1112 (e.g., ROM, EPROM, EEPROM, etc.). A basic input/output system (BIOS) can be stored in the non-volatile memory 1112, and includes the basic routines that facilitate the communication of data and signals between components within the computer 1102, such as during startup. The volatile memory 1110 can also include a high-speed RAM such as static RAM for caching data.
The system bus 1108 provides an interface for system components including, but not limited to, the system memory 1106 to the processing unit(s) 1104. The system bus 1108 can be any of several types of bus structure that can further interconnect to a memory bus (with or without a memory controller), and a peripheral bus (e.g., PCI, PCIe, AGP, LPC, etc.), using any of a variety of commercially available bus architectures.
The computer 1102 further includes machine readable storage subsystem(s) 1114 and storage interface(s) 1116 for interfacing the storage subsystem(s) 1114 to the system bus 1108 and other desired computer components. The storage subsystem(s) 1114 (physical storage media) can include one or more of a hard disk drive (HDD), a magnetic floppy disk drive (FDD), solid state drive (SSD), and/or optical disk storage drive (e.g., a CD-ROM drive DVD drive), for example. The storage interface(s) 1116 can include interface technologies such as EIDE, ATA, SATA, and IEEE 1394, for example.
One or more programs and data can be stored in the memory subsystem 1106, a machine readable and removable memory subsystem 1118 (e.g., flash drive form factor technology), and/or the storage subsystem(s) 1114 (e.g., optical, magnetic, solid state), including an operating system 1120, one or more application programs 1122, other program modules 1124, and program data 1126.
The operating system 1120, one or more application programs 1122, other program modules 1124, and/or program data 1126 can include entities and components of the system 100 of
Generally, programs include routines, methods, data structures, other software components, etc., that perform particular tasks or implement particular abstract data types. All or portions of the operating system 1120, applications 1122, modules 1124, and/or data 1126 can also be cached in memory such as the volatile memory 1110, for example. It is to be appreciated that the disclosed architecture can be implemented with various commercially available operating systems or combinations of operating systems (e.g., as virtual machines).
The storage subsystem(s) 1114 and memory subsystems (1106 and 1118) serve as computer readable media for volatile and non-volatile storage of data, data structures, computer-executable instructions, and so forth. Such instructions, when executed by a computer or other machine, can cause the computer or other machine to perform one or more acts of a method. The instructions to perform the acts can be stored on one medium, or could be stored across multiple media, so that the instructions appear collectively on the one or more computer-readable storage media, regardless of whether all of the instructions are on the same media.
Computer readable media can be any available media that can be accessed by the computer 1102 and includes volatile and non-volatile internal and/or external media that is removable or non-removable. For the computer 1102, the media accommodate the storage of data in any suitable digital format. It should be appreciated by those skilled in the art that other types of computer readable media can be employed such as zip drives, magnetic tape, flash memory cards, flash drives, cartridges, and the like, for storing computer executable instructions for performing the novel methods of the disclosed architecture.
A user can interact with the computer 1102, programs, and data using external user input devices 1128 such as a keyboard and a mouse. Other external user input devices 1128 can include a microphone, an IR (infrared) remote control, a joystick, a game pad, camera recognition systems, a stylus pen, touch screen, gesture systems (e.g., eye movement, head movement, etc.), and/or the like. The user can interact with the computer 1102, programs, and data using onboard user input devices 1130 such a touchpad, microphone, keyboard, etc., where the computer 1102 is a portable computer, for example.
These and other input devices are connected to the processing unit(s) 1104 through input/output (I/O) device interface(s) 1132 via the system bus 1108, but can be connected by other interfaces such as a parallel port, IEEE 1394 serial port, a game port, a USB port, an IR interface, short-range wireless (e.g., Bluetooth) and other personal area network (PAN) technologies, etc. The I/O device interface(s) 1132 also facilitate the use of output peripherals 1134 such as printers, audio devices, camera devices, and so on, such as a sound card and/or onboard audio processing capability.
One or more graphics interface(s) 1136 (also commonly referred to as a graphics processing unit (GPU)) provide graphics and video signals between the computer 1102 and external display(s) 1138 (e.g., LCD, plasma) and/or onboard displays 1140 (e.g., for portable computer). The graphics interface(s) 1136 can also be manufactured as part of the computer system board.
The computer 1102 can operate in a networked environment (e.g., IP-based) using logical connections via a wired/wireless communications subsystem 1142 to one or more networks and/or other computers. The other computers can include workstations, servers, routers, personal computers, microprocessor-based entertainment appliances, peer devices or other common network nodes, and typically include many or all of the elements described relative to the computer 1102. The logical connections can include wired/wireless connectivity to a local area network (LAN), a wide area network (WAN), hotspot, and so on. LAN and WAN networking environments are commonplace in offices and companies and facilitate enterprise-wide computer networks, such as intranets, all of which may connect to a global communications network such as the Internet.
When used in a networking environment the computer 1102 connects to the network via a wired/wireless communication subsystem 1142 (e.g., a network interface adapter, onboard transceiver subsystem, etc.) to communicate with wired/wireless networks, wired/wireless printers, wired/wireless input devices 1144, and so on. The computer 1102 can include a modem or other means for establishing communications over the network. In a networked environment, programs and data relative to the computer 1102 can be stored in the remote memory/storage device, as is associated with a distributed system. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers can be used.
The computer 1102 is operable to communicate with wired/wireless devices or entities using the radio technologies such as the IEEE 802.xx family of standards, such as wireless devices operatively disposed in wireless communication (e.g., IEEE 802.11 over-the-air modulation techniques) with, for example, a printer, scanner, desktop and/or portable computer, personal digital assistant (PDA), communications satellite, any piece of equipment or location associated with a wirelessly detectable tag (e.g., a kiosk, news stand, restroom), and telephone. This includes at least Wi-Fi™ (used to certify the interoperability of wireless computer networking devices) for hotspots, WiMax, and Bluetooth™ wireless technologies. Thus, the communications can be a predefined structure as with a conventional network or simply an ad hoc communication between at least two devices. Wi-Fi networks use radio technologies called IEEE 802.11x (a, b, g, etc.) to provide secure, reliable, fast wireless connectivity. A Wi-Fi network can be used to connect computers to each other, to the Internet, and to wire networks (which use IEEE 802.3-related media and functions).
What has been described above includes examples of the disclosed architecture. It is, of course, not possible to describe every conceivable combination of components and/or methodologies, but one of ordinary skill in the art may recognize that many further combinations and permutations are possible. Accordingly, the novel architecture is intended to embrace all such alterations, modifications and variations that fall within the spirit and scope of the appended claims. Furthermore, to the extent that the term “includes” is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term “comprising” as “comprising” is interpreted when employed as a transitional word in a claim.
