Weighted Parsing

Thiel, Manfred

doi:10.1007/978-3-642-83030-3_5

Cited by 4 publications

(2 citation statements)

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“…Each word is categorized into a lexical class such as noun, verb, and adjective. [17] There are rules specifying the grammar of a sentence. A possible rule set is:…”

Section: Parsing 21 Natural Language Processingmentioning

confidence: 99%

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Knowledge assessment using fuzzy conceptual representation

Cheng

Kilis

Knight

1997

Proceedings of the 1997 ACM Symposium on Applied Computing - SAC '97

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Intelligent Tutoring System (ITS) has existed for many years. One of the problems in ITS research is knowledge proficiency assessment. It is extremely diffficult to assess a student's knowledge accurately.Many researchers have applied different techniques, such as, Bayesian method, for approximation. In addition, many ITSs restrict the student's input by providing interface control or limiting the input set. These unnatural approaches do not allow natural language input from the student. This paper presents an application of fuzzy logic on student knowledge assessment.It also introduces a new knowledge representation, Fuzzy Conceptual Web. Fuzzy Conceptual Web bridges the gaps between different levels of knowledge representation. It also facilitates • free form of input by the student. In addition, the knowledge representation allows for scaling up of the knowledge base.The new approach has been tested on an ITS, called Optimal Physics Tutor, in the domain of mechanical physics. The system has been found to be appropriate and effective in assessing the student's knowledge proficiency level.

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“…Each word is categorized into a lexical class such as noun, verb, and adjective. [17] There are rules specifying the grammar of a sentence. A possible rule set is:…”

Section: Parsing 21 Natural Language Processingmentioning

confidence: 99%

“…Researchers have introduced many methods to resolve the problem. [17] One method is to use keyword to match against the expert's knowledge. Allowing free form of input from the student involves natural language parsing.…”

Section: Introductionmentioning

confidence: 99%