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Authors: Andrey Timofeyev and Ben Choi

Affiliation: Louisiana Tech University, United States

Keyword(s): Automatic Summarization, Semantic Knowledge Base, Text Analysis, Knowledge Discovery, Natural Language Processing.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Context Discovery ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Symbolic Systems

Abstract: This paper describes a knowledge based system for automatic summarization. The knowledge based system creates abstractive summary of texts by generalizing new concepts, detecting main topics, and composing new sentences. The knowledge based system is built on the Cyc development platform, which comprises the world’s largest ontology of common sense knowledge and reasoning engine. The system is able to generate coherent and topically related new sentences by using syntactic structures and semantic features of the given documents, the knowledge base, and the reasoning engine. The system first performs knowledge acquisition by extracting syntactic structure of each sentence in the given documents, and by mapping the words and the relationships of words into Cyc knowledge base. Next, it performs knowledge discovery by using Cyc ontology and inference engine. New concepts are abstracted by exploring the ontology of the mapped concepts. Main topics are identified based on the clustering of the concepts. Then, the system performs knowledge representation for human readers by creating new English sentences to summarize the key concepts and the relationships of the concepts. The structures of the composed sentences extend beyond subject-predicate-object triplets by allowing adjective and adverb modifiers. The system was tested on various documents and webpages. The test results showed that the system is capable of creating new sentences that include generalized concepts not mentioned in the original text and is capable of combining information from different parts of the text to form a summary. (More)

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Paper citation in several formats:
Timofeyev, A. and Choi, B. (2017). Knowledge based Automatic Summarization. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR; ISBN 978-989-758-271-4; ISSN 2184-3228, SciTePress, pages 350-356. DOI: 10.5220/0006580303500356

@conference{kdir17,
author={Andrey Timofeyev. and Ben Choi.},
title={Knowledge based Automatic Summarization},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR},
year={2017},
pages={350-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006580303500356},
isbn={978-989-758-271-4},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR
TI - Knowledge based Automatic Summarization
SN - 978-989-758-271-4
IS - 2184-3228
AU - Timofeyev, A.
AU - Choi, B.
PY - 2017
SP - 350
EP - 356
DO - 10.5220/0006580303500356
PB - SciTePress