International Journal of Knowledge and Web Intelligence
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International Journal of Knowledge and Web Intelligence (3 papers in press)
An enterprise perspective of Web content analysis research: A strategic road-map by Ramesh S. Wadawadagi, Veerappa B. Pagi Abstract: Participating in social networks to create and share content has become ubiquitous part of our daily life. Understanding social media content is top agenda for many firms today. Business analysts and quants are trying hard to discover ways in which enterprises can be benefited by comprehending the data generated through social media such as Facebook, Wikipedia, Blogs, Youtube, and Twitter. This pioneering work may aid business analysts and data scientists with insights into ways to adapt a stable Content Analysis (CA) technique to analyze Web page contents containing user-generated data. As a consequence, we develop an integrated enterprise framework that defines Web Content Analysis (WCA) as a comprehensive and functional layered architecture, and this framework can be used in various levels of the decision-making process. Further, a four dimensional view of comparative analysis of various WCA systems is presented. In conclusion, based on the critical analysis of the literature survey the research asserts the development of integrated enterprise framework for WCA is appropriate. Keywords: User-generated content; Web content analysis; Social media analysis; Semantic Web; Web intelligence. DOI: 10.1504/IJKWI.2017.10010794
Determining the Semantic Orientation of opinion words using typed dependencies for opinion word senses and Sentiwordnet scores from online product reviews by K.C. Ravi Kumar, D. Teja Santosh, B. Vishnu Vardhan Abstract: Opinion words express the information regarding the like and dislike of a user on the target entities such as products and product aspects present in the online reviews. The polarized information collected from the reviews is analyzed by calculating the orientation of the adjectives. The synonymy relation graph is a way to determine the orientation of the adjectives present in the product reviews dataset. It considers the minimum path length between the adjectives under analysis using WordNet synsets. The synonymy relation graph cannot determine the orientations of all the opinion words present in the dataset. In order to evaluate opinion orientation of all the adjectives from the dataset, the synonymy relation graph of WordNet is to be replaced with the Sentiwordnet scores of the opinion words. These scores are provided to the opinion words by finding the contextual clues surrounding the opinion words to disambiguate their sense. The contextual clues are finalized based on the typed dependencies grammatical relations. The distance between the opinion word and the context insensitive seed term (good/bad) is computed by calculating the difference between these scores. This paper addresses advantages of using sentiwordnet scores. This improves the accuracy of the determined opinion word orientations. Keywords: Opinion word; seed term; contextual clues; opinion word sense; opinion word semantic orientation. DOI: 10.1504/IJKWI.2017.10010171
MOSSA : A MOrpho-Semantic knowledge extraction System for Arabic Information Retrieval by Nadia Soudani, Ibrahim Bounhas, Yahya Slimani Abstract: In this paper, we propose to exploit different morpho-semantic resources to enhance Arabic Information Retrieval (IR). We use standardized LMF Arabic dictionaries and Arabic corpora. Our goal by this communication is to take advantage of the different existing resources to extract useful knowledge for Arabic IR. We equally study the impact of the Arabic morphology on IR effectiveness. We aim to disseminate how adding hidden knowledge elicited from such resources to the initial queries can attentively affect the retrieval process and results. Several query expansion strategies are carried based on morphological, semantic and morpho-semantic relations. In addition, combining such knowledge is also studied and evaluated. Moreover, the used knowledge extraction process is driven with an enhanced analysis and disambiguation toolkit that we developed based on MADAMIRA tool. Thus, we consider original short diacritics to reduce ambiguities and we experiment the effect of Part of Speech (POS) disambiguation and tagging in the indexing step. The used knowledge resources can not be directly integrated into the IR system. Many transformations are then performed to get a graph-based representation. This latter represents a powerful formalism to express semantics of texts and to support NLP tools and applications as IR. Several experimental comparisons are handled between the different used knowledge resources and the different carried IR approaches. Keywords: Arabic information retrieval; morpho-semantic knowledge; query expansion; graph-based knowledge representation.