Coling • Acl 2006
نویسندگان
چکیده
A key task in an extraction system for query-oriented multi-document summarisation, necessary for computing relevance and redundancy, is modelling text semantics. In the Embra system, we use a representation derived from the singular value decomposition of a term co-occurrence matrix. We present methods to show the reliability of performance improvements. We find that Embra performs better with dimensionality reduction.
منابع مشابه
Character Language Models for Chinese Word Segmentation and Named Entity Recognition
We describe the application of the LingPipe toolkit (Alias-i 2006) to Chinese word segmentation and named entity recognition. We provide results for the third SIGHAN Chinese language processing bakeoff (Levow 2006). F1 measures on the best performing corpora were .972 for word segmentation and .855 for person/location/organization named-
متن کاملColing • Acl 2006
We describe an unusual data set of thousands of annotated images with interesting sense phenomena. Natural language image sense annotation involves increased semantic complexities compared to disambiguating word senses when annotating text. These issues are discussed and illustrated, including the distinction between word senses and iconographic senses.
متن کاملThe Third International Chinese Language Processing Bakeoff: Word Segmentation and Named Entity Recognition
The Third International Chinese Language Processing Bakeoff was held in Spring 2006 to assess the state of the art in two important tasks: word segmentation and named entity recognition. Twenty-nine groups submitted result sets in the two tasks across two tracks and a total of five corpora. We found strong results in both tasks as well as continuing challenges.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006