A Corpus-based Evaluation of a Domain-specific Text to Knowledge Mapping Prototype

Abstract

<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt; mso-layout-grid-align: none;" align="left"><span style="font-size: 9pt; mso-bidi-font-weight: bold;"><span style="font-family: Times New Roman;">The aim of this paper is to evaluate a Text to Knowledge Mapping (TKM) Prototype. The prototype is domain-specific, the purpose of which is to map instructional text onto a knowledge domain. The context of the knowledge domain is DC electrical circuit. During development, the prototype has been tested with a limited data set from the domain. The prototype reached a stage where it needs to be evaluated with a representative linguistic data set called corpus. A corpus is a collection of text drawn from typical sources which can be used as a test data set to evaluate NLP systems. As there is no available corpus for the domain, we developed and annotated a representative corpus. The evaluation of the prototype considers two of its major components- lexical components and knowledge model. Evaluation on lexical components enriches the lexical resources of the prototype like vocabulary and grammar structures. This leads the prototype to parse a reasonable amount of sentences in the corpus. While dealing with the lexicon was straight forward, the identification and extraction of appropriate semantic relations was much more involved. It was necessary, therefore, to manually develop a conceptual structure for the domain to formulate a domain-specific framework of semantic relations. The framework of semantic relationsthat has resulted from this study consisted of 55 relations, out of which 42 have inverse relations. We also conducted rhetorical analysis on the corpus to prove its representativeness in conveying semantic. Finally, we conducted a topical and discourse analysis on the corpus to analyze the coverage of discourse by the prototype. <em></em></span></span></p&gt

Domain-specific textual commonsense concept acquisition using a corpus

“…Analysis of linguistic information has been limited to some web-based and knowledge-base related tools that cannot operate on any corpus of interest as they have been built upon a specific corpus [18]. Therefore, we developed a parser to extract the sentences from many other linguistic resources in the corpus.…”

“…We developed our commonsense knowledge-base by involving human subjects and a domain-specific corpus proposed in [18]. Zhu et al [1] proposed an experiment that analyzes the difficulty human faces to acquire commonsense knowledge from web corpora.…”

“…We manually developed a commonsense knowledge-base from the text of a DC electrical circuit corpus [18]. This development involves in statistical analysis on the commonsense knowledge of five human subjects and representative text of the corpus.…”

An automatic Text Summarization using feature terms for relevance measure

“…Various works Published has concentrated on different domains where text summarization is used. The domain-specific text summarization then became popular which used corpus for keyword frequencies [4] [7]. This emphasizes on extractive approaches to summarization using statistical methods.…”

“…It is a toolkit [2] used for searching the web and it makes summary of single document and multidocuments [7]. It uses TF-IDF (vector model), Okapi (Probabilistic model) for multidocument summarization and standard query language as relevance feedback.…”