| Patent application number | Description | Published |
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| 20090094020 | Recommending Terms To Specify Ontology Space - In one embodiment, a set of target search terms for a search is received. Candidate terms are selected, where a candidate term is selected to reduce an ontology space of the search. The candidate terms are to a computer to recommend the candidate terms as search terms. In another embodiment, a document stored in one or more tangible media is accessed. A set of target tags for the document is received. Terms are selected, where a term is selected to reduce an ontology space of the document. The terms are sent to a computer to recommend the terms as tags. | 04-09-2009 |
| 20090094207 | Identifying Clusters Of Words According To Word Affinities - In one embodiment, identifying clusters of words includes accessing a record that records affinities. An affinity between a first and second word describes a quantitative relationship between the first and second word. Clusters of words are identified according to the affinities. A cluster comprises words that are sufficiently affine with each other. A first word is sufficiently affine with a second word if the affinity between the first and second word satisfies one or more affinity criteria. A clustering analysis is performed using the clusters. | 04-09-2009 |
| 20090094208 | Automatically Generating A Hierarchy Of Terms - In certain embodiments, generating a hierarchy of terms includes accessing a corpus comprising terms. The following is performed for one or more terms to yield parent-child relationships: one or more parent terms of a term are identified according to directional affinity; and one or more parent-child relationships are established from the parent terms and each term. A hierarchical graph is automatically generated from the parent-child relationships. | 04-09-2009 |
| 20090094231 | Selecting Tags For A Document By Analyzing Paragraphs Of The Document - In one embodiment, assigning tags to a document includes accessing the document, where the document comprises text units that include words. The following is performed for each text unit: a subset of words of a text unit is selected as candidate tags, relatedness is established among the candidate tags, and certain candidate tags are selected according to the established relatedness to yield a candidate tag set for the text unit. Relatedness between the candidate tags of each candidate tag set and the candidate tags of other candidate tag sets is determined. At least one candidate tag is assigned to the document according to the determined relatedness. | 04-09-2009 |
| 20090094233 | Modeling Topics Using Statistical Distributions - In one embodiment, modeling topics includes accessing a corpus comprising documents that include words. Words of a document are selected as keywords of the document. The documents are clustered according to the keywords to yield clusters, where each cluster corresponds to a topic. A statistical distribution is generated for a cluster from words of the documents of the cluster. A topic is modeled using the statistical distribution generated for the cluster corresponding to the topic. | 04-09-2009 |
| 20090204609 | Determining Words Related To A Given Set Of Words - In one embodiment, display of a user entry window of a graphical user interface is initiated. Search terms entered into the user entry window to initiate a first search are received. One or more first search results from a corpus of documents are determined according to the search terms. Display of the search terms at a current search terms window of the graphical user interface is initiated. Display of the first search results at a search results window of the graphical user interface is initiated. Display of the first search suggestions at a search suggestion window of the graphical user interface is initiated. | 08-13-2009 |
