Topic Segmentation Algorithms for Text Summarization and Passage Retrieval: An Exhaustive Evaluation
نویسندگان
چکیده
In order to solve problems of reliability of systems based on lexical repetition and problems of adaptability of languagedependent systems, we present a context-based topic segmentation system based on a new informative similarity measure based on word co-occurrence. In particular, our evaluation with the state-of-the-art in the domain i.e. the c99 and the TextTiling algorithms shows improved results both with and without the identification of multiword units.
منابع مشابه
Unsupervised Topic Segmentation Based on Word Co- occurrence and Multi-Word Units for Text Summarization
Topic Segmentation is the task of breaking documents into topically coherent multi-paragraph subparts. In particular, Topic Segmentation is extensively used in Passage Retrieval and Text Summarization to provide more coherent results by taking into account raw document structure. However, most methodologies are based on lexical repetition that show evident reliability problems or rely on harves...
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Topic segmentation is important for many natural language processing applications such as information retrieval, text summarization... In our work, we are interested in the topic segmentation of textual document. We present a survey of related works particularly C99 and TextTiling. Then, we propose an adaptation of these topic segmenters for textual document written in Arabic language named as ...
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