Semantic Search Exploiting Formal Concept Analysis, Rough Sets, and Wikipedia

Abstract

This article describes how the traditional web search is essentially based on a combination of textual keyword searches with an importance ranking of the documents depending on the link structure of the web. However, one of the dimensions that has not been captured to its full extent is that of semantics. Currently, combining search and semantics gives birth to the idea of the semantic search. The purpose of this article is to present some new methods to semantic search to solve some shortcomings of existing approaches. Concretely, the authors propose two novel methods to semantic search by combining formal concept analysis, rough set theory, and similarity reasoning. In particular, the authors use Wikipedia to compute the similarity of concepts (i.e., keywords). The experimental results show that the authors' proposals perform better than some of the most representative similarity search methods and sustain the intuitions with respect to human judgements.

Deep context of citations using machine-learning models in scholarly full-text articles

“…Overall, our proposed technique contributes to the emerging field of bibliometric-enhanced information retrieval by increasing the query search capabilities of search engines and semantic search approaches on Web 2.0 (De Vocht et al, 2017;Jiang & Yang, 2018). Last but not least, this work can help improve citation-based full-text summarization techniques.…”

Rough set generalization models based information retrieval

“…Since the inception of RST, there has been extensive research on the application of RST in information retrieval. Butthe literature shows the publications of only a few surveys [11,12,13,14,15] contribute considerable knowledge not thoroughgoing and seems restricted in some aspect. [11] focused on fuzzy extension of rough sets in information retrieval.…”

“…[14] investigated the application of RST in IR. In this survey, research gaps and key features of cited frameworks were discussed, but limited number of proposals were included that refrained the survey from exhibiting describe state-of-art.In [15] author presented basic notion and features of RST. Further extension models of RS, their applications, RST application tools and key issues in applying RST to different domains were discussed.…”