Improving Content Selection for Update Summarization with Subtopic-Enriched Sentence Ranking Functions
نویسندگان
چکیده
Update Summarization aims to produce summaries under the assumption that the reader had some knowledge about the topic from the source texts. Usually, traditional approaches of summarization use sentential ranking functions in order to find the most relevant and updated sentences from source-texts. We propose the enriching of these methods with the using of subtopic representation, which are coherent textual segments with one or more sentences in a row. The results of our experiments show that our text representation improves the quality of produced summary and show high recall values.
منابع مشابه
Query-focused Supervised Sentence Ranking for Update Summaries
We present a supervised sentence ranking approach for use in extractive update summarization. We use the same general machine learning approach described in earlier DUC papers, and adapt it to the update summarization task. The system proves adaptable enough to be effective at queryfocused update summaries.
متن کاملPNR2: Ranking Sentences with Positive and Negative Reinforcement for Query-Oriented Update Summarization
Query-oriented update summarization is an emerging summarization task very recently. It brings new challenges to the sentence ranking algorithms that require not only to locate the important and query-relevant information, but also to capture the new information when document collections evolve. In this paper, we propose a novel graph based sentence ranking algorithm, namely PNR, for update sum...
متن کاملFeature expansion for query-focused supervised sentence ranking
We present a supervised sentence ranking approach for use in extractive summarization. Using a general machine learning technique provides great flexibility for incorporating varied new features, which we demonstrate. The system proves quite effective at query-focused multi-document summarization, both for single summaries and for series of update summaries.
متن کاملUpdate Summarization using a Multi-level Hierarchical Dirichlet Process Model
Update summarization is a new challenge which combines salience ranking with novelty detection. Previous researches usually convert novelty detection to the problem of redundancy removal or salience re-ranking, and seldom explore the birth, splitting, merging and death of aspects for a given topic. In this paper, we borrow the idea of evolutionary clustering and propose a three-level HDP model ...
متن کاملSentence Annotation based Enhanced Semantic Summary Generation from Multiple Documents
Problem statement: The goal of document summarization is to provide a summary or outline of manifold documents with reduction in time. Sentence extraction could be a technique that is employed to pick out relevant and vital sentences from documents and presented as a summary. So there is a need to develop more meaningful sentence selection strategy so as to extract most significant sentences. A...
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:
- Int. J. Comput. Linguistics Appl.
دوره 7 شماره
صفحات -
تاریخ انتشار 2016