Abstract: Disclosed herein are techniques for detecting questions in queries. it is determined whether a query comprises a substantially specific question. In one example, past queries related to the current query are used to validate a whether the query comprises the substantially specific question. In another example, query suggestions are used to validate whether the query comprises the substantially specific question.

Abstract: According to one embodiment of the present invention, there is provided a method of selecting an expansion for an acronym in a document of a set of linked documents. The method comprises obtaining for each occurrence of the acronym in the set of linked documents one or more possible acronym expansions and an associated probability that the one or more possible acronym expansions is the correct acronym expansion. The further comprises identifying a sub-set of documents from the set of linked documents in which the acronym occurs. The method further comprises recalculating the associated probabilities for a first occurrence of an acronym in the sub-set of documents based, in part, on the associated probabilities of other occurrences of the acronym in the sub-set of documents and the distance between the first occurrence and the other occurrences.

Abstract: According to one embodiment of the present invention, there is provided a method of selecting an expansion for an acronym in a document of a set of linked documents. The method comprises obtaining for each occurrence of the acronym in the set of linked documents one or more possible acronym expansions and an associated probability that the one or more possible acronym expansions is the correct acronym expansion. The further comprises identifying a sub-set of documents from the set of linked documents in which the acronym occurs. The method further comprises recalculating the associated probabilities for a first occurrence of an acronym in the sub-set of documents based, in part, on the associated probabilities of other occurrences of the acronym in the sub-set of documents and the distance between the first occurrence and the other occurrences.

Abstract: The relevance of documents is automatically determined based upon a weighted tree. Terms considered to be relevant are assigned to the leaf nodes of a tree data structure. A location can also be specified in a leaf node, indicating where in a document the term must appear to be considered relevant. Internal nodes of the tree are assigned operators (e.g., add, maximum or minimum). The connections between nodes are assigned weights. A relevance value for a given document is calculated as a function of occurrence in the document of terms assigned to leaves, operators assigned to internal nodes, and weights assigned to the associated node connections. Weighted trees can be used to process search queries. Documents with high relevance scores calculated against the tree can be returned to a user as the results to a query.