Abstract: Word correlations are estimated using a content-based method, which uses visual features of image representations of the words. The image representations of the subject words may be generated by retrieving images from data sources (such as the Internet) using image search with the subject words as query words. One aspect of the techniques is based on calculating the visual distance or visual similarity between the sets of retrieved images corresponding to each query word. The other is based on calculating the visual consistence among the set of the retrieved images corresponding to a conjunctive query word. The combination of the content-based method and a text-based method may produce even better result.

Abstract: An exemplary method includes providing a music collection of a particular scale, determining a distance parameter for locality sensitive hashing based at least in part on the scale of the music collection and constructing an index for the music collection. Another exemplary method includes providing a song, extracting snippets from the song, analyzing time-varying timbre characteristics of the snippets and constructing one or more queries based on the analyzing. Such exemplary methods may be implemented by a portable device configured to maintain an index, to perform searches based on selected songs or portions of songs and to generate playlists from search results. Other exemplary methods, devices, systems, etc., are also disclosed.

Abstract: A pattern tree is constructed based on a plurality of key-value pairs representing portions of a data set. In some implementations, the pattern tree may be used for learning one or more rules for interacting with a source of the data set.

Abstract: A method and system for identifying the importance of information areas of a display page. An importance system identifies information areas or blocks of a web page. A block of a web page represents an area of the web page that appears to relate to a similar topic. The importance system provides the characteristics or features of a block to an importance function that generates an indication of the importance of that block to its web page. The importance system “learns” the importance function by generating a model based on the features of blocks and the user-specified importance of those blocks. To learn the importance function, the importance system asks users to provide an indication of the importance of blocks of web pages in a collection of web pages.

Abstract: Functionality is described for generating a vocabulary from a source dataset of image items or other non-textual items. The vocabulary serves as a tool for retrieving items from a target dataset in response to queries. The vocabulary has at least one characteristic that allows it to be used to retrieve items from multiple different target datasets. A target dataset can have a different size than the source dataset and/or a different type than the source dataset. The enabling characteristic may correspond to a size of the source dataset above a prescribed minimum number of items and/or a size of the vocabulary above a prescribed minimum number of words.

Abstract: Website design pattern modeling technique embodiments are presented that model a website's design patterns. This can be based on the website's layout elements, its URL tokens, or both. When based on both, the design patterns can be modeled separately using first the layout elements and then the URL tokens, or vice versa. Alternately, the modeling can be based on coupled layout and URL token patterns. In operation, the modeling involves first identifying layout elements and/or URL tokens found on at least some of the pages of the website. The website design patterns are then modeled based on the occurrences of the identified layout elements and/or URL tokens in pages of the website. In cases where a coupled modeling scheme is employed, a modeling technique that exploits the correlations between the layout elements and URL tokens is used.

Abstract: An exemplary method includes providing a music collection of a particular scale, determining a distance parameter for locality sensitive hashing based at least in part on the scale of the music collection and constructing an index for the music collection. Another exemplary method includes providing a song, extracting snippets from the song, analyzing time-varying timbre characteristics of the snippets and constructing one or more queries based on the analyzing. Such exemplary methods may be implemented by a portable device configured to maintain an index, to perform searches based on selected songs or portions of songs and to generate playlists from search results. Other exemplary methods, devices, systems, etc., are also disclosed.

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: 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.

Abstract: Described is using density to efficiently mine co-location patterns, such as closely located businesses frequently found together in business listing databases, geographic search logs, and/or GPS-based data. A data space of such information is geographically partitioned into a grid of cells, with dense cells scanned first. A dynamic upper bound of prevalence measure of co-location patterns is maintained during the scanning process. If the current upper bound is smaller than a threshold, the scanning is stopped, thereby significantly reducing the computation cost for processing many cells, while providing suitable results.

Abstract: Described herein is a technology that facilitates efficient large-scale similarity-based retrieval. In several embodiments documents, images, and/or other multimedia files are compactly represented and efficiently indexed to enable robust search using a long-query in a large-scale corpus. As described herein, these techniques include performing decomposition of a file, e.g., a document or document-like representation. The techniques use dimension reduction to obtain three parts, topic-related words (major semantics), document specific words (minor semantics), and background words, representing the major semantics in a feature vector and the minor semantics as keywords. Using the techniques described, file vectors are matched in a topic model and the results ranked based on the keywords.

Abstract: A “Name Disambiguator” provides various techniques for implementing an interactive framework for resolving or disambiguating entity names (associated with objects such as publications) for entity searches where two or more same or similar names may refer to different entities. More specifically, the Name Disambiguator uses a combination of user input and automatic models to address the disambiguation problem. In various embodiments, the Name Disambiguator uses a two part process, including: 1) a global SVM trained from large sets of documents or objects in a simulated interactive mode, and 2) further personalization of local SVM models (associated with individual names or groups of names such as, for example, a group of coauthors) derived from the global SVM model. The result of this process is that large sets of documents or objects are rapidly and accurately condensed or clustered into ordered sets by that are organized by entity names.

Abstract: Systems and methods for bipartite graph reinforcement modeling to annotate web images are described. In one aspect the systems and methods implement bipartite graph reinforcement modeling operations to identify a set of annotations that are relevant to a Web image. The systems and methods annotate the Web image with the identified annotations. The systems and methods then index the annotated Web image. Responsive to receiving an image search query from a user, wherein the image search query comprises information relevant to at least a subset of the identified annotations, the image search engine service presents the annotated Web image to the user.

Abstract: Techniques are described for online real time text to image translation suitable for virtually any submitted query. Semantic classes and associated analogous items for each of the semantic classes are determined for the submitted query. One or more requests are formulated that are associated with analogous items. The requests are used to obtain web based images and associated surrounding text. The web based images are used to obtain associated near-duplicate images. The surrounding text of images is analyzed to create high-quality text associated with each semantic class of the submitted query. One or more query dependent classifiers are trained online in real time to remove noisy images. A scoring function is used to score the images. The images with the highest score are returned as a query response.

Abstract: An implicit links enhancement system and method for search engines that generates implicit links obtained from mining user access logs to facilitate enhanced local searching of web sites and intranets. Embodiments of the implicit links search enhancement system and method includes extracting implicit links by mining users' access patterns and then using a modified link analysis algorithm to re-rank search results obtained from traditional search engines. More specifically, embodiments of the method include extracting implicit links from a user access log, generating an implicit links graph from the extracted implicit links, and computing page rankings using the implicit links graph. The implicit links are extracted from the log using a two-item sequential pattern mining technique. Search results obtained from a search engine are re-ranked based on an implicit links analysis performed using an updated implicit links graph, a modified re-ranking formula, and at least one re-ranking technique.

Abstract: A system and method of transmit diversity for wireless communication. The system includes a transmitting terminal having a plurality of transmission antennas and a receiving terminal having a plurality of receiving antennas. The method includes analyzing channel state information obtained by the transmitting terminal; selecting an antenna to be one in use from the receiving antennas; matching the selected antenna in use with the wireless signals that are to be transmitted; transmitting wireless signals that are matched to the receiving terminal for being calculated and determining the pre-selected antenna in use, thereby significantly reducing complexities of the receiving terminal.

Abstract: Some implementations generate a mapping function using one or more historic performance indicators for a set of ad-keyword pairs and one or more advertisement metrics extracted from the set of ad-keyword pairs. The mapping function may be applied to map one or more advertisement metrics of a particular ad-keyword pair to determine a quality score for the particular ad-keyword pair. For example, the quality score may be used when determining whether to select an advertisement for display or may be provided as feedback to an advertiser. Additionally, in some implementations, the mapping function may be applied to determine a quality score for a new ad-keyword pair that has not yet accumulated historic information.

Abstract: Some implementations construct a quality score table based on historic data collected for a plurality of ad-keyword pairs. An ad-keyword pair may be selected for determining a quality score. One or more advertisement parameters may be determined for the selected ad-keyword pair. Based on the one or more advertisement parameters, the quality score for the selected ad-keyword pair may be determined from the quality score table. In some implementations, the quality score table is constructed by iteratively cutting a directed graph representing the advertisement parameters and the historic data. Further, in some implementations, the table may be smoothed using a smoothing operation.

Abstract: Some implementations provide techniques for estimating impression numbers. For example, a log of advertisement bidding data may be used to generate and train an impression estimation model. In some implementations, an impression estimation component may use a boost regression technique to determine a predicted impression value range based on a proposed bid received from an advertiser. For example, the predicted impression value range may be determined based on a predicted estimation error. Additionally, in some instances, the predicted impression value range may be evaluated using one or more evaluation metrics.

Abstract: A method and system for determining dominance of the media elements of display pages is provided. The dominance system provides a scoring mechanism for scoring the dominance of media elements of display pages based on features of each media element of the display page. To generate the scores for the media elements of the display page, the dominance system first identifies the media elements and then identifies the features of the media elements. The dominance system then scores the identified media elements using the provided scoring mechanism and the identified features.