Abstract: Methods and computer storage media are provided for generating entries for documents in a forward index. A document and its document identification are received, in addition to static features that are query-independent. The document is parsed into tokens to form a token stream corresponding to the document. Relevant data used to calculate rankings of document is identified and a position of the data is determined. The entry is then generated from the document identification, the token stream of the document, the static features, and the positional information of the relevant data. The entry is stored in the forward index.

Abstract: Methods and computer storage media are provided for generating entries for documents in a forward index. A document and its document identification are received, in addition to static features that are query-independent. The document is parsed into tokens to form a token stream corresponding to the document. Relevant data used to calculate rankings of document is identified and a position of the data is determined. The entry is then generated from the document identification, the token stream of the document, the static features, and the positional information of the relevant data. The entry is stored in the forward index.

Abstract: Methods and computer storage media are provided for generating entries for documents in a forward index. A document and its document identification are received, in addition to static features that are query-independent. The document is parsed into tokens to form a token stream corresponding to the document. Relevant data used to calculate rankings of document is identified and a position of the data is determined. The entry is then generated from the document identification, the token stream of the document, the static features, and the positional information of the relevant data. The entry is stored in the forward index.

Abstract: Methods and systems are provided for using a hybrid-distribution system to identify relevant documents based on a search query. A group of documents is assigned to a particular segment. The group of documents is indexed both by atom and by document to form a reverse index and a forward index. Both indexes are divided amongst each node in that segment so that each node is responsible for storing and accessing a different portion of both the reverse and forward indexes. The reverse index portion is accessed on each of a first set of nodes to identify a first set of documents that is relevant to a particular search query. Document identifications associated with the first set of documents are used to identify a second set of nodes that access their forward index portions to limit the number of relevant documents to a second set of documents.

Abstract: Methods and computer storage media are provided for generating entries for documents in a forward index. A document and its document identification are received, in addition to static features that are query-independent. The document is parsed into tokens to form a token stream corresponding to the document. Relevant data used to calculate rankings of document is identified and a position of the data is determined. The entry is then generated from the document identification, the token stream of the document, the static features, and the positional information of the relevant data. The entry is stored in the forward index.

Abstract: Methods and computer storage media are provided for generating entries for documents in a forward index. A document and its document identification are received, in addition to static features that are query-independent. The document is parsed into tokens to form a token stream corresponding to the document. Relevant data used to calculate rankings of document is identified and a position of the data is determined. The entry is then generated from the document identification, the token stream of the document, the static features, and the positional information of the relevant data. The entry is stored in the forward index.

Abstract: Methods, computer systems, and computer-readable media for generating semantic ranking features using a forward index are provided. A search query is received and is analyzed for one or more semantic units including semantic patterns, topical categories, and entities. A forward index comprising a plurality of documents is accessed and semantic units associated with each of the documents are analyzed. The semantic units include semantic patterns, topical categories, unigrams, bigrams, and entities. Documents who share substantially similar semantic units with the search query are identified, and the ranking of the identified documents is adjusted based on the substantially similar semantic units.

Abstract: Search results are identified and returned in response to search queries by evaluating and pruning candidate documents in multiple stages. The process employs a search index that indexes atoms found in documents and pre-computed scores for document/atom pairs. When a search query is received, atoms are identified from the search query and a reformulated query is generated based on the identified atoms. The reformulated query is used to identify matching documents, and a preliminary score is generated for matching documents using a simplified scoring function and pre-computed scores in the search index. Documents are pruned based on preliminary scores, and the remaining documents are evaluated using a final ranking algorithm that provides a final set of ranked documents, which is used to generate search results to return in response to the search query.

Abstract: Search results are identified and returned in response to search queries by evaluating and pruning candidate documents in multiple stages. The process employs a search index that indexes atoms found in documents and pre-computed scores for document/atom pairs. When a search query is received, atoms are identified from the search query and a reformulated query is generated based on the identified atoms. The reformulated query is used to identify matching documents, and a preliminary score is generated for matching documents using a simplified scoring function and pre-computed scores in the search index. Documents are pruned based on preliminary scores, and the remaining documents are evaluated using a final ranking algorithm that provides a final set of ranked documents, which is used to generate search results to return in response to the search query.

Abstract: Methods and systems are provided for using a hybrid-distribution system to identify relevant documents based on a search query. A group of documents is assigned to a particular segment. The group of documents is indexed both by atom and by document to form a reverse index and a forward index. Both indexes are divided amongst each node in that segment so that each node is responsible for storing and accessing a different portion of both the reverse and forward indexes. The reverse index portion is accessed on each of a first set of nodes to identify a first set of documents that is relevant to a particular search query. Document identifications associated with the first set of documents are used to identify a second set of nodes that access their forward index portions to limit the number of relevant documents to a second set of documents.

Abstract: Methods and computer storage media are provided for generating entries for documents in a forward index. A document and its document identification are received, in addition to static features that are query-independent. The document is parsed into tokens to form a token stream corresponding to the document. Relevant data used to calculate rankings of document is identified and a position of the data is determined. The entry is then generated from the document identification, the token stream of the document, the static features, and the positional information of the relevant data. The entry is stored in the forward index.