Automatic Indexing and Creating Semantic Networks for Agricultural Science Papers in the Polish Language

Wrzeciono, Piotr; Karwowski, Waldemar

doi:10.1109/compsacw.2013.63

Cited by 7 publications

(1 citation statement)

References 2 publications

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“…It also can convey some meaning in a transparent manner. Semantic Network has been widely used in various applications such as medical information retrieval (Koopman, Zuccon, Bruza, Sitbon & Lawley, 2012), web navigation (Amiri, AleAhmad, Rahgozar & Oroumchian, 2008), education (Moise & Ionita, 2008) and agriculture (Wrzeciono, 2013). It has also been widely used in AI applications as it is easy to translate into PROLOG.…”

Section: Object-based Knowledge Representation Approachmentioning

confidence: 99%

Object-Based Knowledge Representation of Female Related Issues From the Holy Quran

Ku-Mahamud

Din

et al. 2014

Journal of Information and Communication Technology

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Focusing on the use of Semantic Network and Conceptual Graph (CG) representations, this paper presents an easy way in understanding concepts discussed in the Holy Quran. Quran is known as the main source of knowledge and has been a major source reference for all types of problems. However understanding the issues and the solution from the Quran is diffi cult due to lack of understanding of Quran literature. Meticulously, the Quran contains much important information related to female. However, this information are scattered and complexly linked. Technically, to extract and present the encapsulated knowledge on female matters in the Quran is a challenging task. Thus, this paper discusses on how to understand and represent the knowledge in an easy way. A total of 18 female terms are identifi ed. Through the terms, the name of surah, verses number and text from the verses are gathered. The texts are then analyzed and clustered into specifi c issues. Result of the analysis that consists of extracted knowledge on female issues is presented in a systematic structure using Semantic Network and CG. The strength and advantages of both approaches are compared, discussed and presented.

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Section: Object-based Knowledge Representation Approachmentioning

confidence: 99%