Экстрактивті қысқаша мазмұндама
Related Papers
Answer Extraction, Semantic Clustering, and Extractive Summarization for Clinical Question Answering
This paper presents a hybrid approach to question answering in the clinical domain that combines techniques from summarization and information retrieval. We tackle a frequently-occurring class of questions that takes …...
Entity-driven Rewrite for Multi-document Summarization
In this paper we explore the benefits from and shortcomings of entity-driven noun phrase rewriting for multi-document sum- marization of news. The approach leads to 20% to 50% different content …...
Generic Text Summarization Using Probabilistic Latent Semantic Indexing
This paper presents a strategy to generate ge- neric summary of documents using Probabilistic Latent Semantic Indexing. Generally a docu- ment contains several topics rather than a single one. Summaries …...
Topic-Driven Multi-Document Summarization with Encyclopedic Knowledge and Spreading Activation
Information of interest to users is often dis- tributed over a set of documents. Users can specify their request for information as a query/topic – a set of one or …...
A Publicly Available Indonesian Corpora for Automatic Abstractive and Extractive Chat Summarization
AbstractIn this paper we report our effort to construct the first ever Indonesian corpora for chat summarization. Specifically, we utilized documents of multi-participant chat from a well known online instant …...
RepSum: Unsupervised Dialogue Summarization based on Replacement Strategy
AbstractIn the field of dialogue summarization, due to the lack of training data, it is often difficult for supervised summary generation methods to learn vital information from dialogue context with …...
Perceived Text Quality and Readability in Extractive and Abstractive Summaries
AbstractWe present results from a study investigating how users perceive text quality and readability in extractive and abstractive summaries. We trained two summarisation models on Swedish news data and used …...