Abstract: Techniques for identifying similar queries based on their overall similarity and partial similarity of time series of frequencies of the queries are provided. To identify queries that are similar to a target query, the query analysis system generates, for each query, an overall similarity score for that query and the target query based on the time series of the query and the target query. The query analysis system also generates, for each query, partial similarity scores for the query and the target query based on various time sub-series of the overall time series of the queries. The query analysis system then identifies queries as being similar to the target query based on the overall similarity scores and the partial similarity scores of the queries.

Abstract: Systems and methods for implementing diverse topic phrase extraction are disclosed. According to one implementation, multiple word candidate phrases are extracted from a corpus and weighed. One or more documents are re-weighed to identify less obvious candidate topics using latent semantic analysis (LSA). Phrase diversification is then used to remove redundancy and select informative and distinct topic phrases.

Abstract: A system and method are disclosed for providing documents related to a search request. The search request may include a search query of one or more keywords, or the search request may be a demographic search query including one or more demographic attributes. An index containing data crawled from publisher's websites, demographic information of registered users, along with the search history of the registered users can be created. Once a search request is received, the search request can be compared to the information stored in the index, and one or more documents related to the request can be provided.

Abstract: A method and system for prioritizing communications based on classifications of sentences within the communications is provided. A sentence classification system may classify sentences of communications according to various classifications such as “sentence mode.” The sentence classification system trains a sentence classifier using training data and then classifies sentences using the trained sentence classifier. After the sentences of a communication are classified, a document ranking system may generate a rank for the communication based on the classifications of the sentences within the communication. The document ranking system trains a document rank classifier using training data and then calculates the rank of communications using the trained document rank classifier.

Abstract: Representing queries and determining similarity of queries based on an autoregressive integrated moving average (“ARIMA”) model is provided. A query analysis system represents each query by its ARIMA coefficients. The query analysis system may estimate the frequency information for a desired past or future interval based on frequency information for some initial intervals. The query analysis system may also determine the similarity of a pair of queries based on the similarity of their ARIMA coefficients. The query analysis system may use various metrics, such as a correlation metric, to determine the similarity of the ARIMA coefficients.

Abstract: Described herein is technology for, among other things, mining pair-based data on the web. The technology involves an online pair-based data mining system as well as an offline SVM training system. By subjecting a pair-based input data to the systems, one may grow a pool of pair-based data which share characteristics of the pair-based input data in more efficient manner.

Abstract: Described herein is technology for, among other things, mining pair-based data on the web. The technology involves an online pair-based data mining system as well as an offline SVM training system. By subjecting a pair-based input data to the systems, one may grow a pool of pair-based data which share characteristics of the pair-based input data in more efficient manner.

Abstract: A method and system for use in information retrieval includes, for each of a plurality of terms, selecting a predetermined number of top scoring documents for the term to form a corresponding document set for the term. When a plurality of terms are received, optionally as a query, the system ranks, using an inverse document frequency algorithm, the plurality of terms for importance based on the document sets for the plurality of terms. Then a number of ranked terms are selected based on importance and a union set is formed based on the document sets associated with the selected number of ranked terms.

Abstract: A method and system for calculating the importance of persons based on interpersonal relationships and prioritizing communications based on importance of participants in the communications is provided. A prioritization system identifies relationships between persons and identifies the importance of a person to other persons based on these relationships. After the prioritization system identifies the importance of persons, the prioritization system can prioritize communications based on the importance of the senders or recipients.

Abstract: Systems and methods are described for an Internet visualization system and related user interfaces. In one implementation, the system analyzes Internet search logs to determine most popular search queries across the world at a current time. A user interface displays a keyword of each of the most popular queries in a single visual display that relates each query to a geographical location of greatest popularity. The system can also filter queries according to demographics. In one implementation the user interface provides a 3-dimensional Internet visualization that adopts an ocean or seascape theme. The ocean floor displays a map of the world, and query bubbles rise from geographical locations on the map. The size and duration of each query bubble denotes the relative popularity of a given query.

Abstract: The claimed subject matter is directed to constructing query hierarchies in response to a query request. To construct a query hierarchy, a list of related candidate queries is generated in response to the received query request. The list of related candidate queries is generated by determining the relative coverage of information shared by the candidate queries and the query request. Relationships between the submitted query request and the candidate queries in the list are determined based upon the extent of relative coverage of information shared by the candidate queries and the query request. A query hierarchy is then constructed to reflect the determined relationships between the query request and the candidate queries.

Abstract: Computer-readable media having computer-executable instructions and apparatuses provide a keyphrase navigation map (KNM) for a document page. Keyphrases are extracted from the document page. Keyphrase clusters are subsequently formed by a measure of relevancy, and a salient keyphrase is determined for each cluster. A thumbnail is formed with tags corresponding to the salient keyphrases. A selected tag is expanded with associated keyphrases. An associated keyphrase may be further selected in order to facilitate the navigation of the document page. The displayed tags on the thumbnail are positioned in accordance with locations of associated keyphrases in the document page.

Abstract: A method and system for adapting search results of a query to the information needs of the user submitting the query is provided. A search system analyzes click-through triplets indicating that a user submitted a query and that the user selected a document from the results of the query. To overcome the large size and sparseness of the click-through data, the search system when presented with an input triplet comprising a user, a query, and a document determines a probability that the user will find the input document important by smoothing the click-through triplets. The search system then orders documents of the result based on the probability of their importance to the input user.

Abstract: A scalable two-pass scalable probabilistic latent semantic analysis (PLSA) methodology is disclosed that may perform more efficiently, and in some cases more accurately, than traditional PLSA, especially where large and/or sparse data sets are provided for analysis. The improved methodology can greatly reduce the storage and/or computational costs of training a PLSA model. In the first pass of the two-pass methodology, objects are clustered into groups, and PLSA is performed on the groups instead of the original individual objects. In the second pass, the conditional probability of a latent class, given an object, is obtained. This may be done by extending the training results of the first pass. During the second pass, the most likely latent classes for each object are identified.

Abstract: Described is an efficient retrieval mechanism that quickly locates documents (e.g., corresponding to online advertisements) based on query term discrimination. A topmost subset (e.g., two) of search terms is selected according to their ranked importance, e.g., as ranked by inverted document frequency. The topmost terms are then used to narrow the number of rows of an inverted query index that are searched to find document identifiers and associated scores, such as computed offline by a BM25 algorithm. For example, for each document identifier of each important term, a fast search within each of the narrowed subset of rows (that also contain that document identifier) may be performed by comparing document identifiers to jump a pointer within each other row, followed by a binary search to locate a particular document. The scores of the set of particular documents may then be used to rank their relative importance for returning as results.

Abstract: Described is a technology by which blocks of web pages may be selected, such as for building a user-personalized web page containing selected blocks. A selection mechanism, such as a browser toolbar add-on, provides a user interface for selecting blocks, and records information about selected blocks. A block tracking mechanism (e.g., a daemon program) uses the information to locate selected blocks of the web pages, including when the web page containing the block is updated with respect to content and/or layout. The block tracking mechanism may update a local gadget that when invoked, such as by browsing to a particular web page, which shows updated versions of the block on a personalized web page. Blocks may be efficiently located by processing trees representing web pages into reduced trees, and then by performing a minimum distance mapping algorithm on the reduced trees.

Abstract: Seed keywords are leveraged to provide expanded keywords that are then associated with relevant advertisers. Instances can also include locating potential advertisers based on the expanded keywords. Inverse lookup techniques are employed to determine which keywords are associated with an advertiser. Filtering can then be employed to eliminate inappropriate keywords for that advertiser. The keywords are then automatically revealed to the advertiser for consideration as relevant search terms for their advertisements. In this manner, revenue for a search engine and/or for an advertiser can be substantially enhanced through the automatic expansion of relevant search terms. Advertisers also benefit by having larger and more relevant search term selections automatically available to them, saving them both time and money.

Abstract: The described systems, methods and data structures are directed to ranking Web pages with hierarchical considerations. The hierarchical structures and the linking relationships of the World Wide Web are used to provide a page importance ranking for Web searches. The linking relationships are aggregated to a high level node at each of the hierarchical structures. A link graph analysis is performed on the aggregated linking relationships to determine the importance of each node. The importance of each node may be propagated to pages associated with that node. For each page, the importance of that page and the importance of the node associated with the page are used to calculate the page importance ranking.

Abstract: A system for calculating the importance of web pages is provided. The web pages are organized hierarchically into collections. The system calculates the importance of each collection based on inter-collection links from a web page in one collection to a web page in another collection. The system then calculates the importance of web pages in the collections with a high calculated importance based on links between the web pages in those collections using, for example, a conventional page rank algorithm. The system may also calculate the importance of web pages in each collection with a low calculated importance separately based on the links between the web pages in the collection using, for example, a conventional page rank algorithm.

Abstract: A system for augmenting click-through data with latent information present in the click-through data for use in generating search results that are better tailored to the information needs of a user submitting a query is provided. The augmentation system creates a three-dimensional matrix with the dimensions of users, queries, and documents. The augmentation system then performs a three-order singular value decomposition of the three-dimensional matrix to generate a three-dimensional core singular value matrix and a left singular matrix for each dimension. The augmentation system finally multiplies the three-dimensional core singular value matrix by the left singular matrices to generate an augmented three-dimensional matrix that explicitly contains the information that was latent in the un-augmented three-dimensional matrix.