Abstract: Many users make use of search engines to locate desired internet content by submitting search queries. For example, a user may search for photos, applications, websites, videos, documents, and/or information regarding people, places, and things. Unfortunately, search engines may provide a plethora of information that a user may be left to sift through to find relevant content. Accordingly, one or more systems and/or techniques for organizing search results are disclosed herein. In particular, user generated content, such as photos, may be retrieved based upon a search query. The user generated content may be grouped into clusters of user generated content having similar features. Search results of the search query may be obtained and organized based upon comparing the search results with the clusters. The organized search results and/or a table of content comprising the clusters may be presented to provide an enhanced user experience.

Abstract: An annotation suggestion platform is described herein. The annotation suggestion platform may comprise a client and a server, where the client captures a media object and sends the captured object to the server, and the server provides a list of suggested annotations for a user to associate with the captured media object. The user may then select which of the suggested metadata is to be associated or stored with the captured media. In this way, a user may more easily associate metadata with a media object, facilitating the media object's search and retrieval. The server may also provide web page links related to the captured media object. A user interface for the annotation suggestion platform is also described herein, as are optimizations including indexing and tag propagation.

Abstract: Techniques for identifying near-duplicates of a media object and associating metadata of the near-duplicates with the media object are described herein. One or more devices implementing the techniques are configured to identify the near duplicates based at least on similarity attributes included in the media object. Metadata is then extracted from the near-duplicates and is associated with the media object as descriptors of the media object to enable discovery of the media object based on the descriptors.

Abstract: Described herein is a technology that facilitates learning interests for advertising based on automated analysis of images. In several embodiments a person's interests are automatically learned based on the person's photographs for targeted advertising. Techniques are described that facilitate automatically detecting a user's interest from images and suggesting user-targeted ads. As described herein, these techniques include computer-annotating images with learned tags, performing topic learning to obtain an interest model, and performing advertisement matching and ranking based on the interest model.

Abstract: A simultaneous semantic and structure threaded discussion modeling system and method for generating a model of a discussion thread and using the model to mine data from the discussion thread. Embodiments of the system and method generate a model that contains both semantic terms and structure terms. The model simultaneously models both semantics and structure of the discussion thread. A model generator includes a semantic module generates two semantic terms for the model and a structure module generates two structure terms for the model. The generator combines the two semantic terms and the two structure terms to generate the simultaneous semantic and structure model. Embodiments of the system and method include an applications module, which contains three application that use the model to reconstruct reply relations among posts in the discussion thread, identify junk posts in the discussion thread, and find experts in each sub-board of web forums.

Abstract: In some implementations, a plurality of first questions and corresponding first answers are identified at a community question-answer (CQA) site as a plurality of first question-answer (q-a) pairs. A query thread comprised of a second question and a plurality of candidate second answers is selected for making a determination of answer quality. A set of the first questions that are similar to the second question are identified from the plurality of first questions. First linking features between the identified set of first questions and their corresponding first answers are used for determining an analogy with second linking features between the second question and candidate answers for ranking the candidate answers.

Abstract: A method for advertising in response to an image search. One or more keywords may be received. The keywords may be for searching one or more images on the network. The images may be retrieved based on the keywords. One or more advertisements may be selected based on a first visual content of the images and a second visual content of the one or more advertisements. The one or more of the advertisements may be displayed.

Abstract: The present invention discloses a search-based segmentation method and device for a language without a word boundary tag. The inventive method includes the steps of: a. providing at least one search engine with a segment of a text including at least one segment; b. searching for the segment through the at least one search engine, and returning search results; and c. selecting a word segmentation approach for the segment in accordance with at least part of the returned search results. The invention solves the problems of word segmentation for a language without a word boundary tag, and thus combat the limitations of the prior art in terms of flexibility, dependence upon coverage of dictionaries, available training data corpuses, processing of a new word, etc.

Abstract: Annotation by search is described. In one aspect, a data store is searched for images that are semantically related to a baseline annotation of a given image and visually similar to the given image. The given image is then annotated with common concepts of annotations associated with at least a subset of the semantically and visually related images.