-
Robin, J.; McKeown, K.: Empirically designing and evaluating a new revision-based model for summary generation (1996)
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- Abstract
- Presents a system for summarizing quantitative data in natural language, focusing on the use of a corpus of basketball game summaries, drawn from online news services, to empirically shape the system design and to evaluate the approach. Initial corpus analysis revealed characteristics of textual summaries that challenge the capabilities of current language generation systems. A revision based corpus analysis was used to identify and encode the revision rules of the system. Presents a quantitative evaluation, using several test corpora, to measure the robustness of the new revision based model
- Date
- 6. 3.1997 16:22:15
-
Goh, A.; Hui, S.C.: TES: a text extraction system (1996)
0.04
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- Abstract
- With the onset of the information explosion arising from digital libraries and access to a wealth of information through the Internet, the need to efficiently determine the relevance of a document becomes even more urgent. Describes a text extraction system (TES), which retrieves a set of sentences from a document to form an indicative abstract. Such an automated process enables information to be filtered more quickly. Discusses the combination of various text extraction techniques. Compares results with manually produced abstracts
- Date
- 26. 2.1997 10:22:43
- Source
- Microcomputers for information management. 13(1996) no.1, S.41-55
-
Jones, P.A.; Bradbeer, P.V.G.: Discovery of optimal weights in a concept selection system (1996)
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- Source
- Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
-
Haag, M.: Automatic text summarization : Evaluation des Copernic Summarizer und mögliche Einsatzfelder in der Fachinformation der DaimlerCrysler AG (2002)
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- Abstract
- An evaluation of the Copernic Summarizer, a software for automatically summarizing text in various data formats, is being presented. It shall be assessed if and how the Copernic Summarizer can reasonably be used in the DaimlerChrysler Information Division in order to enhance the quality of its information services. First, an introduction into Automatic Text Summarization is given and the Copernic Summarizer is being presented. Various methods for evaluating Automatic Text Summarization systems and software ergonomics are presented. Two evaluation forms are developed with which the employees of the Information Division shall evaluate the quality and relevance of the extracted keywords and summaries as well as the software's usability. The quality and relevance assessment is done by comparing the original text to the summaries. Finally, a recommendation is given concerning the use of the Copernic Summarizer.
-
Vanderwende, L.; Suzuki, H.; Brockett, J.M.; Nenkova, A.: Beyond SumBasic : task-focused summarization with sentence simplification and lexical expansion (2007)
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- Abstract
- 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 accomplish this task comprises four main components: a generic extractive summarization system, a topic-focusing component, sentence simplification, and lexical expansion of topic words. This paper details each of these components, together with experiments designed to quantify their individual contributions. We include an analysis of our results on two large datasets commonly used to evaluate task-focused summarization, the DUC2005 and DUC2006 datasets, using automatic metrics. Additionally, we include an analysis of our results on the DUC2006 task according to human evaluation metrics. In the human evaluation of system summaries compared to human summaries, i.e., the Pyramid method, our system ranked first out of 22 systems in terms of overall mean Pyramid score; and in the human evaluation of summary responsiveness to the topic, our system ranked third out of 35 systems.
- Source
- Information processing and management. 43(2007) no.6, S.1606-1618
-
Jiang, Y.; Meng, R.; Huang, Y.; Lu, W.; Liu, J.: Generating keyphrases for readers : a controllable keyphrase generation framework (2023)
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- Abstract
- With the wide application of keyphrases in many Information Retrieval (IR) and Natural Language Processing (NLP) tasks, automatic keyphrase prediction has been emerging. However, these statistically important phrases are contributing increasingly less to the related tasks because the end-to-end learning mechanism enables models to learn the important semantic information of the text directly. Similarly, keyphrases are of little help for readers to quickly grasp the paper's main idea because the relationship between the keyphrase and the paper is not explicit to readers. Therefore, we propose to generate keyphrases with specific functions for readers to bridge the semantic gap between them and the information producers, and verify the effectiveness of the keyphrase function for assisting users' comprehension with a user experiment. A controllable keyphrase generation framework (the CKPG) that uses the keyphrase function as a control code to generate categorized keyphrases is proposed and implemented based on Transformer, BART, and T5, respectively. For the Computer Science domain, the Macro-avgs of , , and on the Paper with Code dataset are up to 0.680, 0.535, and 0.558, respectively. Our experimental results indicate the effectiveness of the CKPG models.
- Date
- 22. 6.2023 14:55:20
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.7, S.759-774
-
Wang, W.; Hwang, D.: Abstraction Assistant : an automatic text abstraction system (2010)
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- Abstract
- In the interest of standardization and quality assurance, it is desirable for authors and staff of access services to follow the American National Standards Institute (ANSI) guidelines in preparing abstracts. Using the statistical approach an extraction system (the Abstraction Assistant) was developed to generate informative abstracts to meet the ANSI guidelines for structural content elements. The system performance is evaluated by comparing the system-generated abstracts with the author's original abstracts and the manually enhanced system abstracts on three criteria: balance (satisfaction of the ANSI standards), fluency (text coherence), and understandability (clarity). The results suggest that it is possible to use the system output directly without manual modification, but there are issues that need to be addressed in further studies to make the system a better tool.
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.9, S.1790-1799
-
Oh, H.; Nam, S.; Zhu, Y.: Structured abstract summarization of scientific articles : summarization using full-text section information (2023)
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- Abstract
- The automatic summarization of scientific articles differs from other text genres because of the structured format and longer text length. Previous approaches have focused on tackling the lengthy nature of scientific articles, aiming to improve the computational efficiency of summarizing long text using a flat, unstructured abstract. However, the structured format of scientific articles and characteristics of each section have not been fully explored, despite their importance. The lack of a sufficient investigation and discussion of various characteristics for each section and their influence on summarization results has hindered the practical use of automatic summarization for scientific articles. To provide a balanced abstract proportionally emphasizing each section of a scientific article, the community introduced the structured abstract, an abstract with distinct, labeled sections. Using this information, in this study, we aim to understand tasks ranging from data preparation to model evaluation from diverse viewpoints. Specifically, we provide a preprocessed large-scale dataset and propose a summarization method applying the introduction, methods, results, and discussion (IMRaD) format reflecting the characteristics of each section. We also discuss the objective benchmarks and perspectives of state-of-the-art algorithms and present the challenges and research directions in this area.
- Date
- 22. 1.2023 18:57:12
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.2, S.234-248
-
Wu, Y.-f.B.; Li, Q.; Bot, R.S.; Chen, X.: Finding nuggets in documents : a machine learning approach (2006)
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- Date
- 22. 7.2006 17:25:48
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.740-752
-
Kim, H.H.; Kim, Y.H.: Generic speech summarization of transcribed lecture videos : using tags and their semantic relations (2016)
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- Date
- 22. 1.2016 12:29:41
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.2, S.366-379
-
Bateman, J.; Teich, E.: Selective information presentation in an integrated publication system : an application of genre-driven text generation (1995)
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- Source
- Information processing and management. 31(1995) no.5, S.753-767
-
Pinto, M.: Engineering the production of meta-information : the abstracting concern (2003)
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- Source
- Journal of information science. 29(2003) no.5, S.405-418
-
Gomez, J.; Allen, K.; Matney, M.; Awopetu, T.; Shafer, S.: Experimenting with a machine generated annotations pipeline (2020)
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- Abstract
- The UCLA Library reorganized its software developers into focused subteams with one, the Labs Team, dedicated to conducting experiments. In this article we describe our first attempt at conducting a software development experiment, in which we attempted to improve our digital library's search results with metadata from cloud-based image tagging services. We explore the findings and discuss the lessons learned from our first attempt at running an experiment.
-
McKeown, K.; Robin, J.; Kukich, K.: Generating concise natural language summaries (1995)
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- Abstract
- Description of the problems for summary generation, the applications developed (for basket ball games - STREAK and for telephone network planning activity - PLANDOC), the linguistic constructions that the systems use to convey information concisely and the textual constraints that determine what information gets included
- Source
- Information processing and management. 31(1995) no.5, S.703-733
-
Paice, C.D.: Automatic abstracting (1994)
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- Source
- Encyclopedia of library and information science. Vol.53, [=Suppl.16]
-
Ouyang, Y.; Li, W.; Li, S.; Lu, Q.: Intertopic information mining for query-based summarization (2010)
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- Abstract
- In this article, the authors address the problem of sentence ranking in summarization. Although most existing summarization approaches are concerned with the information embodied in a particular topic (including a set of documents and an associated query) for sentence ranking, they propose a novel ranking approach that incorporates intertopic information mining. Intertopic information, in contrast to intratopic information, is able to reveal pairwise topic relationships and thus can be considered as the bridge across different topics. In this article, the intertopic information is used for transferring word importance learned from known topics to unknown topics under a learning-based summarization framework. To mine this information, the authors model the topic relationship by clustering all the words in both known and unknown topics according to various kinds of word conceptual labels, which indicate the roles of the words in the topic. Based on the mined relationships, we develop a probabilistic model using manually generated summaries provided for known topics to predict ranking scores for sentences in unknown topics. A series of experiments have been conducted on the Document Understanding Conference (DUC) 2006 data set. The evaluation results show that intertopic information is indeed effective for sentence ranking and the resultant summarization system performs comparably well to the best-performing DUC participating systems on the same data set.
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.1062-1072
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Maybury, M.T.: Generating summaries from event data (1995)
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- Abstract
- Summarization entails analysis of source material, selection of key information, condensation of this, and generation of a compct summary form. While there habe been many investigations into the automatic summarization of text, relatively little attention has been given to the summarization of information from structured information sources such as data of knowledge bases, despite this being a desirable capability for a number of application areas including report generation from databases (e.g. weather, financial, medical) and simulation (e.g. military, manufacturing, aconomic). After a brief introduction indicating the main elements of summarization and referring to some illustrative approaches to it, considers pecific issues in the generation of text summaries of event data, describes a system, SumGen, which selects key information from an event database by reasoning about event frequencies, frequencies of relations between events, and domain specific importance measures. Describes how Sum Gen then aggregates similar information and plans a summary presentations tailored to stereotypical users
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- Information processing and management. 31(1995) no.5, S.735-751
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Kuhlen, R.: Abstracts, abstracting : intellektuelle und maschinelle Verfahren (1990)
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- Source
- Grundlagen der praktischen Information und Dokumentation. 3. Aufl. Hrsg.: M. Buder u.a. Bd.1
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Craven, T.C.: Presentation of repeated phrases in a computer-assisted abstracting tool kit (2001)
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- Source
- Information processing and management. 37(2001) no.2, S.221-230
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Endres-Niggemeyer, B.: SimSum : an empirically founded simulation of summarizing (2000)
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- Source
- Information processing and management. 36(2000) no.4, S.659-682
