Dynamic Coreference-Based Summarization
نویسندگان
چکیده
\Ve ha.ve developed a query-sensitive text summarization technology \Vell suited for the task of determining whether a. document is relevant to <'-" query. Enoug;h of the docurnent is displayed for the user to determine whether the document should l:H~ read in its entirety. Evaluations indicate that sununarics are classif-ied for relevauce uearly as well as full documents. This approach i.s based on the concept that a good SltJnrnary will repn-)sent each of the topics in the query and is n'alized by ~electing smltcnc<-!S from the document until all the phrases in the query which are represented in the sumiHa.ry are (covered.' A phrase in th<:; docu. ' Jllcnt is considered to cover a phraf:le in the qu(~r:Y if it is cmeferent \Vith it. This approach maxirnizes the space of <!ntities reta.incd in th(:: summ<Jxy with minimal rednnda.ncy. 'rhe software is built upon the CAMP NLP spt.cm [2].
منابع مشابه
Using Coreference Links and Sentence Compression in Graph-based Summarization
Recent years have shown that graphs are an adequate text representation model for summarization. For this years’ TAC update summarization challenge, we extended our graph-based summarization system with coreference relations and sentence compression. Our results show that using coreference relations did not result in a significant performance gain; sentence compression had a negative effect on ...
متن کاملCorpus based coreference resolution for Farsi text
"Coreference resolution" or "finding all expressions that refer to the same entity" in a text, is one of the important requirements in natural language processing. Two words are coreference when both refer to a single entity in the text or the real world. So the main task of coreference resolution systems is to identify terms that refer to a unique entity. A coreference resolution tool could be...
متن کاملFuzzy Coreference Resolution for Summarization
We present a fuzzy-theory based approach to coreference resolution and its application to text summarization. Automatic determination of coreference between noun phrases is fraught with uncertainty. We show how fuzzy sets can be used to design a new coreference algorithm which captures this uncertainty in an explicit way and allows us to define varying degrees of coreference. The algorithm is e...
متن کاملUsing Knowledge-poor Coreference Resolution for Text Summarization
We present a system that produces 10-word summaries based on the single summarization strategy of outputting noun phrases representing the most important text entities (as represented by noun phrase coreference chains). The coreference chains were computed using fuzzy set theory combined with knowledgepoor corefernce heuristics.
متن کاملExperiments on Semantic-based Clustering for Cross-document Coreference
We describe clustering experiments for cross-document coreference for the first Web People Search Evaluation. In our experiments we apply agglomerative clustering to group together documents potentially referring to the same individual. The algorithm is informed by the results of two different summarization strategies and an offthe-shelf named entity recognition component. We present different ...
متن کاملContext-based Multi-Document Summarization using Fuzzy Coreference Cluster Graphs
Constructing focused, context-based multi-document summaries requires an analysis of the context questions, as well as their corresponding document sets. We present a fuzzy cluster graph algorithm that finds entities and their connections between context and documents based on fuzzy coreference chains and describe the design and implementation of the ERSS summarizer implementing these ideas.
متن کامل