| Patent application number | Description | Published |
| 20080208840 | Diverse Topic Phrase Extraction - 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. | 08-28-2008 |
| 20080208841 | CLICK-THROUGH LOG MINING - Click-through log mining is described. Raw search click-through log data is processed to generate ordered query keywords, utilizing an algorithm to expand user-submitted keywords to include high frequency user queries, managing the keywords for a keyword expansion file, analyzing the algorithm performance on a bidding criteria, and identifying related phrases with similar page-click behaviors for advertisements. | 08-28-2008 |
| 20080215574 | Efficient Retrieval Algorithm by Query Term Discrimination - An exemplary method 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; receiving a plurality of terms, optionally as a query; ranking the plurality of terms for importance based at least in part on the document sets for the plurality of terms where the ranking comprises using an inverse document frequency algorithm; selecting a number of ranked terms based on importance where each selected, ranked term comprises its corresponding document set wherein each document in a respective document set comprises a document identification number; forming a union set based on the document sets associated with the selected number of ranked terms; and, for a document identification number in the union set, scanning a document set corresponding to an unselected term for a matching document identification number. Various other exemplary systems, methods, devices, etc. are also disclosed. | 09-04-2008 |
| 20080215997 | WEBPAGE BLOCK TRACKING GADGET - An exemplary web browser system includes a selection module for selecting a webpage block and recording information about a selected webpage block; a tracking module for tracking changes to a selected webpage block based at least in part on the recorded information for that webpage block; and a display module for displaying a selected webpage block wherein the tracking module updates the display module as to changes to the selected webpage block. Various other exemplary systems, methods, devices are also disclosed. | 09-04-2008 |
| 20080281834 | Block tracking mechanism for web personalization - 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. | 11-13-2008 |
| 20080288348 | Ranking online advertisements using retailer and product reputations - A method for ranking online advertisements using retailer reputation and product reputation. In one implementation, a query may be received. Advertisements may be selected by determining a level of relevance between the query and each advertisement and selecting the advertisements with a level of relevance above a pre-determined level of relevance. A predicted reputation for a retailer and a predicted reputation for a product may be retrieved for each of the selected advertisements. The selected advertisements may then be ranked based on the predicted reputation for the retailer and the predicted reputation of the product. The ranking of the selected advertisements may be accomplished by calculating a ranking score for each selected advertisement based on the retailer predicted reputation and the product predicted reputation. The selected advertisements may then be displayed according to the ranking. | 11-20-2008 |
| 20080288481 | Ranking online advertisement using product and seller reputation - Described is a technology by which online advertisements for returning with a query response are ranked according to reputation. The reputation may correspond to a product or service and/or seller reputation. In one example, a set of relevant advertisement items are located and ranked using reputation data as a factor. For example, for each item, a ranking value is based on a mathematical combination of a product reputation score, a seller reputation score and a relevance score, with the items ranked by their computed values. The scores may be weighted differently. The reputation data may be mined from a review source, such as customer reviews available on the web. In one example implementation, a 3-gram model that considers terms in the review along with the two terms proceeding each term is used to analyze the reviews to determine whether each review is positive or negative with respect to the reputation. | 11-20-2008 |
| 20080288483 | Efficient retrieval algorithm by query term discrimination - 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. | 11-20-2008 |
| 20090063461 | USER QUERY MINING FOR ADVERTISING MATCHING - Systems and methods to determine relevant keywords from a user's search query sessions are disclosed. The described method includes identifying search session logs of a user, segmenting the search session logs into one or more search sessions. After the segmentation, the search sessions are analyzed to compose a list of semantically relevant keyword sets including at least a first keyword set and a second keyword set. The described method further includes determining a semantic relevance between the first and second keyword sets according to the frequency at which the first and second keyword sets are reported in the query results and displaying one or more semantically high relevant keyword sets after being filtered by a threshold. | 03-05-2009 |