发明名称 |
Text-based automatic content classification and grouping |
摘要 |
A closed-caption [101], is passed to a natural language analysis tool [102]. Noun phrases and proper nouns in closed-captions are extracted and saved in a file [103]. The noun phrase file is passed to a word-code translation tool [104] and each different word is assigned a unique code from a dictionary. The output [105] of the word-code translation tool [104] provides source data for story classification [110] and grouping [114]. For story classification [110], training [107] and testing [111] examples are generated by another tool [106]. A story classification knowledge network [109] is generated from training examples [107] input to the training module and modified thereafter for each new story. Class prediction [112] and knowledge base modification can be realized interactively on a news organizer platform. Relevant story grouping [114] takes a story location [105] and corresponding story grouping files [113] and determines a group [115] for the new story.
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申请公布号 |
EP1291790(A2) |
申请公布日期 |
2003.03.12 |
申请号 |
EP20020255600 |
申请日期 |
2002.08.09 |
申请人 |
SIEMENS CORPORATE RESEARCH, INC. |
发明人 |
ZHU, WEIYU;LIOU, SHIH-PING;TOKLU, CANDEMIR |
分类号 |
G06F17/30;(IPC1-7):G06F17/30 |
主分类号 |
G06F17/30 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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