摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
A method and system for determining the relevance of a document to a query based on surrogate content is provided. The relevance system associates queries with documents. The relevance system calculates the relevance of a document to a query based at least in part on the similarity of the associated queries to the query. When multiple queries are associated with a document, the relevance system may provide a weight for each query for calculating a combined relevance score for the associated queries.
摘要:
In an embodiment, a method of predicting an active user's rating for an item is disclosed. A database of users may be sorted into clusters. The data associated with the users in each cluster may be smoothed to filling in ratings for items that the users have not personally rated. An active user may then be compared to a set of users, where the set may be all or some portion of the database, to determine the K users that are most similar to the active user. The ratings of the K users regarding the item may be used to predict the active user's rating for the item. In an embodiment, the rating of each of the K users is assigned a confidence value associated with whether the user personally rated the item or if the rating was generated by the data smoothing process.
摘要:
Methods for determining a predictive rating are disclosed. In an embodiment, an active user is compared to a set of clusters. One or more of the clusters are determined to be most similar to the active user. From the one or more clusters, K users are determined to be most similar to the active user. Prior ratings for an item by the K users may be used to predict a rating for the item for the active user.
摘要:
Methods for determining a predictive rating are disclosed. In an embodiment, an active user is compared to a set of clusters. One or more of the clusters are determined to be most similar to the active user. From the one or more clusters, K users are determined to be most similar to the active user. Prior ratings for an item by the K users may be used to predict a rating for the item for the active user.
摘要:
A method and system for detecting whether an outgoing communication contains confidential information or other target information is provided. The detection system is provided with a collection of documents that contain confidential information, referred to as “confidential documents.” When the detection system is provided with an outgoing communication, it compares the content of the outgoing communication to the content of the confidential documents. If the outgoing communication contains confidential information, then the detection system may prevent the outgoing communication from being sent outside the organization. The detection system detects confidential information based on the similarity between the content of an outgoing communication and the content of confidential documents that are known to contain confidential information.
摘要:
A method and system for classifying messages of a discussion thread as questions is provided. A classification system generates a classifier to classify messages of discussion threads as question messages or non-question messages. The system trains the classifier using the feature vectors and input classifications derived from a training set of discussion threads. After the classifier is trained, the classification system uses the classifier to classify messages within a corpus of discussion threads as question or non-question messages. To classify a message, the classification system generates a feature vector for the messages and submits that feature vector to the classifier. The classifier generates a score for the message indicating a likelihood that the message is a question message.