Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/11946
ชื่อเรื่อง: Causal web determination from texts
ผู้แต่ง: Pechsiri C.
Keeratipranon N.
Piriyakul I.
วันที่เผยแพร่: 2020
บทคัดย่อ: The research aim is to determine a causal web from downloaded guru web-board documents. The causal web which benefits a diagnosis service assistant of a problem-solving system consists of several cause-effect pair sequences where each cause-effect pair has a cause-effect relation and the last cause-effect pair of each cause-effect pair sequence has the same effect concept. Each causative/effect concept is expressed by an elementary discourse unit or a simple sentence. The research has three problems; how to determine the cause-effect pair with an overlap problem between a causative-verb concept set and an effect-verb concept set, how to determine cause-effect pair sequences including causative/effect boundary determination, and how to determine the causal web on the extracted cause-effect pair sequences without redundant sequences. We use a word co-occurrence to represent a sentence’s event/state with a causative/effect concept. We then propose using a self-Cartesian product on a collected word co-occurrence set and Naïve Bayes including categorized verb groups to extract each cause-effect pair sequence including the boundary determination without the verb-concept-overlap influence. And we use a dynamic template matching technique to determine the causal web without the redundancy. The research result has a high percentage correctness of the causal web determination. © 2020 J. Adv. Inf. Technol.
URI: https://ir.swu.ac.th/jspui/handle/123456789/11946
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087897405&doi=10.12720%2fjait.11.2.64-70&partnerID=40&md5=a8c80eef94f6ee505f673080470c4d48
ISSN: 17982340
Appears in Collections:Scopus 1983-2021

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