کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
402624 676968 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Incremental learning from news events
ترجمه فارسی عنوان
یادگیری افزوده از رویدادهای خبری
کلمات کلیدی
خبرها و رویدادها، سلسله مراتب موضوع یادگیری افزایشی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

As news events on the same subject occur, our knowledge about the subject will accumulate and become more comprehensive. In this paper, we formally define the problem of incremental knowledge learning from similar news events on the same subject, where each event consists of a set of news articles reporting about it. The knowledge is represented by a topic hierarchy presenting topics at different levels of granularity. Though topic (hierarchy) mining from text has been researched a lot, incremental learning from similar events remains under developed. In this paper, we propose a scalable two-phase framework to incrementally learn a topic hierarchy for a subject from events on the subject as the events occur. First, we recursively construct a topic hierarchy for each event based on a novel topic model considering the named entities and entity types in news articles. Second, we incrementally merge the topic hierarchies through top-down hierarchical topic alignment. Extensive experimental results on real datasets demonstrate the effectiveness and efficiency of the proposed framework in terms of both qualitative and quantitative measures.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 89, November 2015, Pages 618–626
نویسندگان
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