Patent application number | Description | Published |
20090024554 | Method For Matching Electronic Advertisements To Surrounding Context Based On Their Advertisement Content - A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that focuses on capturing subtler linguistic associations between the surrounding content and the content of the advertisement. The system of the present invention implements this goal by means of simple and efficient semantic association measures dealing with lexical collocations such as conventional multi-word expressions like “big brother” or “strong tea”. The semantic association measures are used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the semantic association measures for the advertisements and the surrounding context. | 01-22-2009 |
20090094200 | Method for Admission-controlled Caching - A method of caching the results of a search engine query divides a search engine cache into two parts, controlled and uncontrolled, and determines, through an admission policy, to which part the query results should be cached. In one implementation, the admission policy estimates whether a query is likely to be frequent or infrequent in the future by analyzing various features of the query. | 04-09-2009 |
20090094416 | SYSTEM AND METHOD FOR CACHING POSTING LISTS - A method of caching posting lists to a search engine cache calculates the ratios between the frequencies of the query terms in a past query log and the sizes of the posting lists for each term, and uses these ratios to determine which posting lists should be cached by sorting the ratios in decreasing order and storing to the cache those posting lists corresponding to the highest ratio values. Further, a method of finding an optimal allocation between two parts of a search engine cache evaluates a past query stream based on a relationship between various properties of the stream and the total size of the cache, and uses this information to determine the respective sizes of both parts of the cache. | 04-09-2009 |
20090112840 | Method For Selecting Electronic Advertisements Using Machine Translation Techniques - A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that takes advantage of machine translation technologies. The system of the present invention implements this goal by means of simple and efficient machine translation features that are extracted from the surrounding context to match with the pool of potential advertisements. Machine translation features used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the machine translation features measures for the advertisements and the surrounding context. | 04-30-2009 |
20090157652 | METHOD AND SYSTEM FOR QUANTIFYING THE QUALITY OF SEARCH RESULTS BASED ON COHESION - A method and system for quantifying the quality of search results from a search engine based on cohesion. The method and system include modeling a set of search engine search results as a cluster and measuring the cohesion of the cluster. In an embodiment, the cohesion of the cluster is the average similarity between the cluster elements to a centroid vector. The centroid vector is the average of the weights of the vectors of the cluster. The similarity between the centroid vector and the cluster's elements is the cosine similarity measure. Each document in the set of search results is represented by a vector where each cell of the vector represents a stemmed word. Each cell has a cell value which is the frequency of the corresponding stemmed word in a document multiplied by a weight that takes into account the location of the stemmed word within the document. | 06-18-2009 |
20090204753 | SYSTEM FOR REFRESHING CACHE RESULTS - A system and method for refreshing a cache based on query responses provided by a searching system in response to queries, includes providing a cache entry for each unique query, if space is available in the cache, and assigning a temperature value to each cache entry based on a frequency of occurrence of the corresponding query An age value is assigned to each cache entry based on a time of last refresh or creation of the corresponding query response. The age of the cache entries is periodically updated, and the temperature of a cache entry is updated when a corresponding query reoccurs. If system resources are available, the query response of a cache entry is refreshed based on the temperature and age of the cache entry. If resources are not available, the refreshing is limited. | 08-13-2009 |
20090265230 | RANKING USING WORD OVERLAP AND CORRELATION FEATURES - A system for and method for ranking results. The system includes a server configured to receive a query and an advertisement engine configured to receive the query from the server. The advertisement engine ranks advertisements based on various features, including at least one word overlap feature and a correlation feature. | 10-22-2009 |
20090265290 | OPTIMIZING RANKING FUNCTIONS USING CLICK DATA - A system for optimizing machine-learned ranking functions based on click data. The system determines the weighting for each feature of a plurality of features according to a learning model based on the click data. The system selects an element from a plurality of elements for display on a web page based on the weighting of each feature of the plurality of features. The system may rank the items to form a list on the web page based on the weighted features in order of inferred relevance according to the online learning model. | 10-22-2009 |
20100010895 | PREDICTION OF A DEGREE OF RELEVANCE BETWEEN QUERY REWRITES AND A SEARCH QUERY - A predictor for determining a degree of relevance between a query rewrite and a search query is provided. The predictor may receive a search query from a user via a terminal and identify a set of candidate query rewrites associated with the search query. The predictor may then extract a set of features from advertisements associated with the query rewrites and the search query and determine a degree of relevance between the advertisements and the search query based on a prediction model. The predictor may then determine the degree of relevance between the rewrites and the search query based on the determined degree of relevance between the advertisements and the search query. | 01-14-2010 |
20100094853 | SYSTEM AND METHODOLOGY FOR A MULTI-SITE SEARCH ENGINE - Techniques for query processing in a multi-site search engine are described. During an indexing phase, each site of a multi-site search engine indexes a set of assigned web resources and each site calculates, for each term in the set of assigned web resources, a site-specific upper bound ranking score on the contribution of the term to the search engine ranking function for a query containing the term. During a propagation phase, all sites exchange their site-specific upper bound ranking scores with each other. In response to a site receiving a query, the site determines the set of locally matching resources and compares the ranking score of a locally matching resource with the site-specific upper bound ranking scores for the terms of the query that were received during the propagation phase and determines whether to communicate the query to other sites. By exchanging appropriately defined site-specific upper bound ranking scores, the site initially receiving the query can determine whether the locally matching resources would be identical to the resources obtained from a single-site search system without having to communicate the query to each of the other sites. | 04-15-2010 |
20100131493 | LIGHTNING SEARCH BOOKMARK - Disclosed are methods and apparatus for automatically storing and generating bookmarks. In one embodiment, a search query is received. Information identifying a bookmark representing the search query is automatically stored in association with a set of bookmarks. Search results corresponding to the search query are automatically obtained and provided, where the search results identify one or more documents. When one of the documents is selected, a link to the selected one of the documents is automatically stored in association with the bookmark. | 05-27-2010 |
20100131495 | LIGHTNING SEARCH AGGREGATE - Disclosed are methods and apparatus for executing a search query. In accordance with one embodiment, a search query is obtained. The search query is classified into one or more of a plurality of categories. The search query is executed for each of the one or more of the plurality of categories. Search results corresponding to the search query are obtained for each of the one or more of the plurality of categories. The search results are then provided for each of the one or more of the plurality of categories. | 05-27-2010 |
20100161145 | SEARCH ENGINE DESIGN AND COMPUTATIONAL COST ANALYSIS - A computer implemented system for search engine facility architecting and design. The system estimates the costs of power and networking based on system parameters, such as average CPU utilization, connection time, and bytes transferred over the network. Regional distribution of facilities may be evaluated to take into account the various parameters and optimize the cost and speed of the systems being designed. The parameters used in analyzing and formulating an architecture are independent of a particular indexing or query processing technique. | 06-24-2010 |
20110087680 | Method for Selecting Electronic Advertisements Using Machine Translation Techniques - A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that takes advantage of machine translation technologies. The system of the present invention implements this goal by means of simple and efficient machine translation features that are extracted from the surrounding context to match with the pool of potential advertisements. Machine translation features used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the machine translation features measures for the advertisements and the surrounding context. | 04-14-2011 |
20120109758 | Method For Matching Electronic Advertisements To Surrounding Context Based On Their Advertisement Content - A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that focuses on capturing subtler linguistic associations between the surrounding content and the content of the advertisement. The system of the present invention implements this goal by means of simple and efficient semantic association measures dealing with lexical collocations such as conventional multi-word expressions like “big brother” or “strong tea”. The semantic association measures are used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the semantic association measures for the advertisements and the surrounding context. | 05-03-2012 |
20130013628 | LIGHTNING SEARCH BOOKMARK - Disclosed are methods and apparatus for automatically storing and generating bookmarks. In one embodiment, a search query is received. Information identifying a bookmark representing the search query is automatically stored in association with a set of bookmarks. Search results corresponding to the search query are automatically obtained and provided, where the search results identify one or more documents. When one of the documents is selected, a link to the selected one of the documents is automatically stored in association with the bookmark. | 01-10-2013 |