| 摘要 |
A computer system and methods are disclosed for automatically discovering topics and building a hierarchical topic structure, and for tagging and categorizing contents in a document or other natural language contents. The disclosed methods include steps for obtaining terms that best represent the topics in a text content, and building a hierarchical representation of topics of different levels or topic-comment relationships, and folder-subfolder structures. The methods further include obtaining, identifying, and selecting terms representing different degrees of informational importance based on the grammatical roles, parts of speech, and semantic attributes associated with the terms, using the terms to represent topics in the document, to automatically tag the document, to rank search results, and to build a category structure based on the selected terms. |
| 主权项 |
1. A computer system, comprising:
a processor operable to receive a text content comprising a plurality of terms, each term comprising one or more words or phrases; tokenize the text content into a plurality of terms, each term comprising one or more words or phrases; identifying a first semantic attribute or a first part of speech, wherein the first semantic attribute is selected from the group of semantic attributes consisting of at least an action, a thing, a person, an agent of an action, a recipient of an action or a thing, a state of an object, a mental state of a person, a physical state of a person, a positive or negative opinion, a name of a product, a name of a service, a name of an organization, wherein the first part of speech is selected from the group of parts of speech consisting of at least a noun or a pronoun, a transitive or intransitive verb or modal verb or link verb, an adjective, an adverb, a preposition, an article, a conjunction; identify a first term in the text content, wherein the first term is associated with the first semantic attribute or the first part of speech; identify a second term in the text content, wherein the second term is not associated with the first semantic attribute or the first part of speech; associate an importance measure to the first term, based at least on the first semantic attribute or the first part of speech, to mark the first term as bearing more importance than the second term in representing a topic or an information focus in the text content; extract the first term based on the importance measure; and output the first term; when the first term is output, the function of the first term includes being a tag or a label to represent a topic or a summary of the text content, or a category node; when the first term is output and displayed, the display format includes the font type, size, color, shape, position, or orientation of the first term based on the importance measure; when the text content containing the first term is made searchable using a query or is associated with a search index to produce a search result, the search result is ranked based at least on the importance measure. |
