Abstract: A keyterm search is a method of searching a database for subsets of the database that are relevant to an input query. First, a number of relational models of subsets of a database are provided. A query is then input. The query can include one or more keyterms. Next, a gleaning model of the query is created. The gleaning model of the query is then compared to each one of the relational models of subsets of the database. The identifiers of the relevant subsets are then output.

Abstract: A phrase search is a method of searching a database for subsets of the database that are relevant to an input query. First, a number of relational models of subsets of a database are provided. A query is then input. The query can include one or more sequences of terms. Next, a relational model of the query is created. The relational model of the query is then compared to each one of the relational models of subsets of the database. The identifiers of the relevant subsets are then output.

Abstract: A phrase discovery is a method of identifying sequences of terms in a database. First, a selection of one or more relevant sequences of terms, such as relevant text, is provided. Next, several shorter sequences of terms, such as phrases, are extracted from the provided relevant sequences of terms. The extracted sequences of terms are then reduced through a culling process. A gathering process then emphasizes the more relevant of the extracted and culled sequences of terms and de-emphasizes the more generic of the extracted and culled sequences of terms. The gathering process can also include iteratively retrieving additional selections of relevant sequences (e.g., text), extracting and culling additional sequences of terms (e.g., phrases), emphasizing and de-emphasizing extracted and culled sequences of terms and accumulating all gathered sequences of terms. The resulting gathered sequences of terms are then output.

Abstract: A phrase generation is a method of generating sequences of terms, such as phrases, that may occur within a database of subsets containing sequences of terms, such as text. A database is provided and a relational model of the database is created. A query is then input. The query includes a term or a sequence of terms or multiple individual terms or multiple sequences of terms or combinations thereof. Next, several sequences of terms that are contextually related to the query are assembled from contextual relations in the model of the database. The sequences of terms are then sorted and output. Phrase generation can also be an iterative process used to produce sequences of terms from a relational model of a database.

Abstract: A keyterm search is a method of searching a database for subsets of the database that are relevant to an input query. First, a number of relational models of subsets of a database are provided. A query is then input. The query can include one or more keyterms. Next, a gleaning model of the query is created. The gleaning model of the query is then compared to each one of the relational models of subsets of the database. The identifiers of the relevant subsets are then output.

Abstract: A phrase search is a method of searching a database for subsets of the database that are relevant to an input query. First, a number of relational models of subsets of a database are provided. A query is then input. The query can include one or more sequences of terms. Next, a relational model of the query is created. The relational model of the query is then compared to each one of the relational models of subsets of the database. The identifiers of the relevant subsets are then output.

Abstract: A phrase discovery is a method of identifying sequences of terms in a database. First, a selection of one or more relevant sequences of terms, such as relevant text, is provided. Next, several shorter sequences of terms, such as phrases, are extracted from the provided relevant sequences of terms. The extracted sequences of terms are then reduced through a culling process. A gathering process then emphasizes the more relevant of the extracted and culled sequences of terms and de-emphasizes the more generic of the extracted and culled sequences of terms. The gathering process can also include iteratively retrieving additional selections of relevant sequences (e.g., text), extracting and culling additional sequences of terms (e.g., phrases), emphasizing and de-emphasizing extracted and culled sequences of terms and accumulating all gathered sequences of terms. The resulting gathered sequences of terms are then output.

Abstract: A phrase generation is a method of generating sequences of terms, such as phrases, that may occur within a database of subsets containing sequences of terms, such as text. A database is provided and a relational model of the database is created. A query is then input. The query includes a term or a sequence of terms or multiple individual terms or multiple sequences of terms or combinations thereof. Next, several sequences of terms that are contextually related to the query are assembled from contextual relations in the model of the database. The sequences of terms are then sorted and output. Phrase generation can also be an iterative process used to produce sequences of terms from a relational model of a database.