Information Processing and Management: an International Journal

This paper reviews research on automatic summarising in the last decade. This work has grown, stimulated by technology and by evaluation programmes. The paper uses several frameworks to organise the review, for summarising itself, for the factors ...

This article introduces a new task-based evaluation measure called Relevance Prediction that is a more intuitive measure of an individual's performance on a real-world task than interannotator agreement. Relevance Prediction parallels what a user does ...

We show some limitations of the ROUGE evaluation method for automatic summarization. We present a method for automatic summarization based on a Markov model of the source text. By a simple greedy word selection strategy, summaries with high ROUGE-scores ...

Recent years have seen increased interest in text summarization with emphasis on evaluation of prototype systems. Many factors can affect the design of such evaluations, requiring choices among competing alternatives. This paper examines several major ...

The high quality evaluation of generated summaries is needed if we are to improve automatic summarization systems. Although human evaluation provides better results than automatic evaluation methods, its cost is huge and it is difficult to reproduce the ...

We present a new paradigm for the automatic creation of document headlines that is based on direct transformation of relevant textual information into well-formed textual output. Starting from an input document, we automatically create compact ...

This article examines the application of two single-document sentence compression techniques to the problem of multi-document summarization-a ''parse-and-trim'' approach and a statistical noisy-channel approach. We introduce the multi-candidate ...

The paper focuses on a particular approach to automatic sentence compression which makes use of a discriminative sequence classifier known as Conditional Random Fields (CRF). We devise several features for CRF that allow it to incorporate information on ...

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel ...

In recent years, there has been increased interest in topic-focused multi-document summarization. In this task, automatic summaries are produced in response to a specific information request, or topic, stated by the user. The system we have designed to ...

Generating summaries that meet the information needs of a user relies on (1) several forms of question decomposition; (2) different summarization approaches; and (3) textual inference for combining the summarization strategies. This novel framework for ...

We argue that the quality of a summary can be evaluated based on how many concepts in the original document(s) that can be preserved after summarization. Here, a concept refers to an abstract or concrete entity or its action often expressed by diverse ...

We propose a new method for using anaphoric information in Latent Semantic Analysis (LSA), and discuss its application to develop an LSA-based summarizer which achieves a significantly better performance than a system not using anaphoric information, ...

This paper presents a model that incorporates contemporary theories of tense and aspect and develops a new framework for extracting temporal relations between two sentence-internal events, given their tense, aspect, and a temporal connecting word ...

Keywords can be considered as condensed versions of documents and short forms of their summaries. In this paper, the problem of automatic extraction of keywords from documents is treated as a supervised learning task. A lexical chain holds a set of ...

The potential of summary personalization is high, because a summary that would be useless to decide the relevance of a document if summarized in a generic manner, may be useful if the right sentences are selected that match the user interest. In this ...

Due to a large variety of noisy information embedded in Web pages, Web-page classification is much more difficult than pure-text classification. In this paper, we propose to improve the Web-page classification performance by removing the noise through ...

In the field of law there is an absolute need for summarizing the texts of court decisions in order to make the content of the cases easily accessible for legal professionals. During the SALOMON and MOSAIC projects we investigated the summarization and ...

Text summarization is a method for data reduction. The use of text summarization enables users to reduce the amount of text that must be read while still assimilating the core information. The data reduction offered by text summarization is particularly ...

Most knowledge accumulated through scientific discoveries in genomics and related biomedical disciplines is buried in the vast amount of biomedical literature. Since understanding gene regulations is fundamental to biomedical research, summarizing all ...

Field Association (FA) terms are a limited set of discriminating terms that can specify document fields. Document fields can be decided efficiently if there are many relevant FA terms in that documents. An earlier approach built FA terms dictionary ...

References to parts of structured documents use their structure to locate the piece of document which is the reference target. On the other hand, XML has become an increasingly important language for structured documents. One of its most important ...