Patent Application
20090164266
To assist a user in making a decision about purchasing a product or a service, many users consult opinions provided by other users or by editorial staffs. However, such opinions may be limited to a specific product or service or may only provide a limited opinion, and thus, the user may not be provided with adequate and/or accurate information to make informed decisions.
Embodiments of the present invention relate to aggregating opinion data by category. Such a method comprises, in part, receiving information, such as from a web page, that comprises opinion data, where the opinion data relates to one or more entities (e.g., products, services, people, brands, etc.). At least one category associated with the information is determined, and the information is aggregated by category to produce aggregated category opinion data, which then may be provided for presentation to the user. The opinion data may also be aggregated and provided by entity, and further by feature of the entity or category. Additionally, in some embodiments, the opinion data may be indexed, and may then be accessed when a search request is made by a user.
In another embodiment of the present invention, a method for displaying aggregated opinion data is provided that comprises, in part, displaying a first graphical user interface that presents aggregated opinion data by category, where the category includes one or more entities; determining whether the user requests an entity presented on the first graphical user interface; and, if so, displaying a second graphical user interface that presents opinion data related to the requested entity.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
The present invention is described in detail below with reference to the attached drawing figures, wherein:
The subject matter of the present invention is described with specificity herein to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described in this document, in conjunction with other present or future technologies. Moreover, although the terms “step” and/or “block” may be used herein to connote different elements of methods employed, the terms should not be interpreted as implying any particular order among or between various steps herein disclosed unless and except when the order of individual steps is explicitly described.
Embodiments of the present invention relate to aggregating opinion data and providing aggregated opinion data to a user. Aggregating opinion data, where the opinion data relates to one or more entities, provides the user with sentiment information and allows the user to view opinion data from various sources at a category level and/or an entity level. Within each level, the user may further view the opinion data by feature, so that, if a particular feature is of importance to the user, this may be displayed. In some embodiments, the aggregated opinion data is provided via a graphical user interface that displays the opinion data as aggregated by category. The user may then view a second graphical user interface displaying opinion data for a specific entity within the category.
In one embodiment of the invention, one or more computer storage media performing a method for aggregating opinion data is provided. The method comprises, in part, receiving information that comprises opinion data related to one or more entities; determining at least one category associated with the information; aggregating the information by category to produce aggregated category opinion data; and providing the aggregated category opinion data for presentation.
In another embodiment of the invention, a method for displaying aggregated opinion data is provided, comprising, in part, displaying a first graphical user interface presenting opinion data aggregated by category, where the category comprises one or more entities; determining whether a user requests opinion data associated with one of the entities; and if the user requests one of the entities, displaying a second graphical user interface presenting opinion data associated with the requested entity.
In yet another embodiment, one or more computer storage media performing a method for providing aggregated opinion data is provided. The method comprises, in part, receiving a search query associated with a category, where the category comprises one or more entities; extracting information that comprises opinion data related to the category, where the information is associated with at least one feature; aggregating the information to produce aggregated category opinion data; and providing the aggregated category opinion data by feature for presentation.
Having briefly described an overview of embodiments of the present invention, an exemplary operating environment suitable for use in implementing embodiments of the present invention is described below.
Referring to the drawings in general, and initially to
The invention may be described in the general context of computer code or machine-useable instructions, including computer-executable instructions such as program components, being executed by a computer or other machine, such as a personal data assistant or other handheld device. Generally, program components including routines, programs, objects, components, data structures, and the like, refer to code that performs particular tasks, or implements particular abstract data types. Embodiments of the present invention may be practiced in a variety of system configurations, including hand-held devices, consumer electronics, general-purpose computers, specialty-computing devices, and the like. Embodiments of the present invention may also be practiced in distributed computing environments where tasks are performed by remote-processing devices that are linked through a communications network.
With continued reference to
Computing device 100 typically includes a variety of computer-readable media. By way of example, and not limitation, computer-readable media may comprise Random Access Memory (RAM); Read Only Memory (ROM); Electronically Erasable Programmable Read Only Memory (EEPROM); flash memory or other memory technologies; CD-ROM, digital versatile discs (DVD) or other optical or holographic media; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices; or any other medium that can be used to encode desired information and be accessed by computing device 100.
Memory 112 includes computer-storage media in the form of volatile and/or nonvolatile memory. The memory may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical-disk drives, and the like. Computing device 100 includes one or more processors that read data from various entities such as memory 112 or I/O components 120. Presentation component(s) 116 present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, etc. I/O ports 118 allow computing device 100 to be logically coupled to other devices including I/O components 120, some of which may be built in. Illustrative components include a microphone, joystick, game advertisement, satellite dish, scanner, printer, wireless device, and the like.
Turning now to
Computing system 200 includes a user device 210, a category aggregation engine 212, and a data store 214, in communication with one another via a network 216. The network 216 may include, without limitation, one or more local area networks (LANs) and/or wide area networks (WANs). Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet. Accordingly, the network 216 is not further described herein.
The data store 214 may be configured to store information associated with opinion data, as more fully described below. It will be understood and appreciated by those of ordinary skill in the art that the information stored in the data store 214 may be configurable and may include information relevant to opinion data that may be extracted for indexing. Further, though illustrated as a single, independent component, data store 214 may, in fact, be a plurality of data stores, for instance, a database cluster, portions of which may reside on a computing device associated with the category aggregation engine 212, the user device 210, another external computing device (not shown), and/or any combination thereof.
Each of the category aggregation engine 212 and the user device 210 shown in
As shown in
The receiving component 218 is configured for receiving opinion data from a variety of sources. Opinion data, as used herein, refers to data comprising sentiment information associated with one or more entities. An entity may be any specific subject for which opinion data may be received, such as specific products, services, people, brands, etc. Opinion data may represent opinions of third-party users (e.g., from user feedback), experts, and the like. Accordingly, the receiving component 218 is configured for receiving information from a variety of sources, such as a plurality of web pages, each source having opinion data associated therewith. Once received by the receiving component 218, the opinion data may be stored, for instance, in association with data store 214, and/or indexed as desired. Indexing is described more fully herein below. It will be appreciated that information may be received from various sources. In one embodiment, crawled documents or documents that are obtained by a web-crawler, are received. In another embodiment, feed documents, or documents of known relevance and format that are fed into the system, are received.
The category determining component 220 is configured for determining one or more categories associated with the opinion data received by receiving component 218. As used herein, a category refers to a term describing a group classifying the entity. For example, if the source provided opinion data for an entity, such as a Microsoft® Zune™, the category associated with this source of opinion data may be mp3 players. Accordingly, there could be multiple entities in each category. So, in this example, other mp3 players (e.g., an Apple® Ipod™) may be other entities associated with the mp3 player category.
It will be understood that an entity may be classified in more than one category, and further that the category may vary in its scope and may encompass another category. For example, “digital cameras” as a category may be more broadly classified as a “cameras” category, and “SLR digital cameras” could be another category with a more narrow scope. In an embodiment of the invention, the scope of each category is configurable, and may be adjusted for the user. For example, if the user was an experienced photographer, the user may desire opinion data on SLR digital cameras. The opinion data may then be aggregated at varying levels of category specificity to suit the needs of the user.
One skilled in the art will appreciate that a brand may also be a category. By way of example, without limitation, if the category was “Toyota,” entities could include the various models of cars sold by Toyota. Or, if the category was “Levi's,” entities could include different styles of jeans manufactured by Levi's.
The designation of the scope desired by the user may be determined in various ways. In one embodiment, the user may be asked, after requesting opinion data of a category, about their knowledge or skill level relevant to that category. In further embodiments, algorithms may be used to automatically determine such a designation. For example, the text entered by a user for a query may be analyzed and the relevant results may be used to determine the category. So, by way of example, without limitation, if a user searched for “330i,” relevant results produced might be for BMW coupes and sedans. From these results, it is determined that the user may want opinion data for categories, such as “luxury coupes” or “luxury sedans.”
The entity determining component 230 is configured for determining one or more entities associated with the opinion data received by receiving component 218. One or more entities are determined so that, in one embodiment, the opinion data may be aggregated by entity. Determination of one or more entities associated with the opinion data may also be used by the category determining component 220 to determine the one or more categories associated with the opinion data.
The opinion extracting component 222 is configured to extract features and sentiment information from the opinion data. One skilled in the art will appreciate that any suitable method may be used for extracting opinion data. Opinion data may include any sentiment information contained in a source, such as, for example, positive, negative, or neutral feedback. Alternatively, opinion data may be based on a scaled system (e.g., a ranking of one to five stars).
As discussed above, both crawled documents (e.g., documents that are obtained by a web-crawler) and feed documents (e.g., documents of known relevance and format that are fed into the system) may be accessed for opinion extraction. In one embodiment, the opinion extracting component 222 determines whether the crawled documents express opinions about the specific entity or entities for which aggregated opinion data is desired. Documents determined to be relevant, along with the feed documents of known relevance, are subjected to opinion extraction where components of an input document are identified (e.g., reviewer name, review body, review rating, etc.) that can aid in subsequent opinion identification.
Further, the sentiment information is associated with at least one feature. A feature, as used herein, refers to any aspect of an entity that may be described or for which an opinion may be rendered. For example, if the source information relates to an entity such as the Zune, various features associated with the source information could include sound quality, ease of use, battery life, appearance, etc. If, instead of a product, the category comprised entities related to a customer service (e.g., plumber), exemplary features associated with the opinion data may be reliability, customer service, and knowledge. If, for example, the given entity was a person, such as a president, a writer, an entertainer, etc., features associated with such an entity may include personal appearance, speaking ability, intelligence, and the like. It will be understood that a source may provide opinion data associated with only one feature or with more than one feature for a given entity. Thus, for example, a source may only include opinion data relating to a single feature, such as the sound quality of the Zune, or may include opinion data on several features, such as sound quality and battery life.
The search request receiving component 226 is configured for receiving a search request for which satisfying content is desired. By way of example, the search request may be received at a user interface as the result of user input. It will be understood and appreciated by those of ordinary skill in the art that multiple methods exist by which a user may input a search request. For instance, search requests may be input, by way of example only, utilizing a keyboard, joystick, trackball, touch-advertisement, or the like. Alternative user interfaces known in the software industry are contemplated by the invention. The search request is typically a user-initiated action or response that is received at a user interface, as discussed above. Examples of a request are a click, click-through, or selection by a user, e.g., human user or robotic user; however, it is understood and appreciated by one of ordinary skill in the art that a request may take any number of forms of indication at a web page. Further, it is contemplated by the present invention that a robotic user may be any non-human operator (i.e., an internet bot, web bot program, virus, robot, web crawler, web spidering program, or any software applications that run automated tasks over the Internet), which is an artificial agent that, by its actions, conveys a sense that it has intent or agency of its own. Even further, a human user is contemplated as being a human, but also, an entity (virtual or physical) acting under the present intent of a human operator. Upon receiving a search request, indexed, extracted opinion data may be queried to determine if satisfying data is present.
The presenting component 228 is configured for presenting aggregated opinion data related to at least one category to a user. Typically such presentation will be by way of display in association with a user interface. Exemplary user interfaces are discussed with respect to
Referring now to
In embodiments of the invention, the aggregating component 224 may comprise a controversy factor component 310, a value determining component 312, and a ranking component 314. The controversy factor component 310 is configured to determine the controversy factor associated with opinion data received that relates to an entity. As used herein, a controversy factor refers to the most important feature for user when considering the opinion data on the entity. A controversy factor may be based on various factors and may be configured as necessary for the user. Exemplary methods include the feature or features most frequently discussed by multiple sources of opinion data (i.e., features that have received the most number of aggregated comments), or the feature or features that receive a varied of amount of positive and negative feedback. The controversy factor is used in the determination of what features to present to a user. That is, opinion data related to numerous features of an entity or category may be received. By determining the controversy factor, the features that are most important to the user can be determined, and thus aggregated and presented to the user.
In one embodiment, the value determining component 312 in
The ranking component 314 is configured to rank the entities in a category, based on the opinion data, in order to determine the entities that perform the best and worst in regards to a specific feature. For example, when the opinion data is aggregated by category and the user selects a feature associated with the category, those entities that have been ranked as top performers in that specific feature are presented. The poor performers that are ranked lowest for the entities may also be presented to the user. In another embodiment, the ranking component 314 ranks brands based on the aggregated opinion data. So, by way of example, without limitation, the top brands may be presented to the user.
Turning now to
Subsequently, in block 414, the category and/or entity associated with the opinion data is determined, for instance, by category determining component 220 or entity determining component 230 in
It will be understood by those of ordinary skill in the art that the order of steps shown in the method 400 of
In
As previously mentioned, aggregated opinion data may be presented utilizing a variety of user interface features. Such features may include, by way of example only, novel user interface elements presented with respect to a web (or other source) page. Without limitation, a number of user interface features are described herein below with reference to FIGS. 5 and 6. It will be understood by those of ordinary skill in the art that a number of other user interface features may be utilized to present aggregated opinion data in accordance with embodiments hereof and that the user interface features shown in
Referring now to
In the embodiment of the user interface shown in
Furthermore, the entities are ranked based on predetermined standards, as discussed above. Note that display area 514 displays the best performers 526 for the sound quality feature. If poor performers 528 were selected, the worst performers for that feature would be presented. In another embodiment, where the entity was a brand, the top brands may be presented, as well as the poor brands.
Referring now to
Referring now to
The present invention has been described in relation to particular embodiments, which are intended in all respects to be illustrative rather than restrictive. Alternative embodiments will become apparent to those of ordinary skill in the art to which the present invention pertains without departing from its scope.
From the foregoing, it will be seen that this invention is one well adapted to attain all of the ends and objects set forth above, together with other advantages which are obvious and inherent to the system and method. It will be understood that certain features and subcombinations are of utility and may be employed without reference to other features and subcombinations. This is contemplated by and is within the scope of the claims.
