Guided summarization is an extension of query-focused multidocument summarization. We proposed a novel ranking algorithm, Topic Guided Manifold Ranking with Sink Points (TMSP) for guided summarization tasks of TAC2010. TMSP is a topic extended version of Manifold Ranking with Sink Points (MRSP), which handles the Update Summarization tasks of TAC2009 well. We adopt the TMSP and MRSP methods to ...

Summarization of software artifacts is an ongoing field of research among the software engineering community due to the benefits that summarization provides like saving of time and efforts in various software engineering tasks like code search, duplicate bug reports detection, traceability link recovery, etc. Summarization is to produce short and concise summaries. The paper presents the review...

While surgical videos are valuable support material for activities around surgery, their summarization demands great amounts of time from surgeons, resulting in the production very few videos. We study practices involving video to motivate and inform future design tools summarization. Through interviews observations a field study, we find that (1) summaries provide an important being used self-...

In this paper, we propose a novel context inference-based approach for sentences ordering in mult i-document summarization application. Our method first detects whether or not two summarizat ion sentences should be adjacent according to the similarity between one summarizat ion sentence and the context of the other one, and then it computes the reliability of the adjacent summarization sentence...

In this paper we consider a method for extraction of sets of semantically similar language expressions representing different participants of the text story – thematic chains. The method is based on the structural organization of news clusters and exploits comparison of various contexts of words. The word contexts are used as a basis for extracting multiword expressions and constructing themati...

In this paper we consider a method for extraction of sets of semantically similar language expressions representing different participants of the text story – thematic nodes. The method is based on the structural organization of news clusters and exploits comparison of various contexts of words. The word contexts are used as a basis for multiword expression extraction and thematic node construc...

As enormous amount of electronic documents on the Web have been increasing, the necessity of automatic summarization has also been increasing to help people grasp the essential points of the documents. Many summarization techniques dealing with single document and multi-documents have been studied. However, due to the increase of the documents which report the change of topics along a timeline,...

In this paper we study the effectiveness of applying sentence compression on an extraction based multi-document summarization system. Our results show that pure syntactic-based compression does not improve system performance. Topic signature-based reranking of compressed sentences does not help much either. However reranking using an oracle showed a significant improvement remains possible.

Most of the text summarization research carried out to date has been concerned with the summarization of short documents (e.g., news stories, technical reports), and very little work if any has been done on the summarization of very long documents. In this paper, we try to address this gap and explore the problem of book summarization. We introduce a new data set specifically designed for the e...