Young Hee Jung ¹, Kinam Park ², Jeong Min Chae ¹, Soon Young Jung ¹

Affiliations
1 Department of Computer Science of Education, Korea University, KR
2 Department of Computer Software Engineering, Soonchunhyang University, KR

Abstract

A coordinate noun phrases connects two words or phrases together via a coordinate conjunction. The duplicate words of conjunctions are mainly omitted. This structure often occurs in the science literature. And this makes it difficult to understand of the sentence. Our research is motivated by the need to reduce the costs of misunderstandings that can occur during NER. We propose a method for resolving coordinate noun phrases with simple or complex ellipses using rules and dataset. And we describe a method to automatically build dataset. This method is applicable to a general-purpose in various fields. Our dataset effectively is used to distinguish between high and low modifier attachment. We reported on a set of experimental results to evaluate the performance of our approach. The results show that our system can efficiently resolve coordinate noun phrases. And we are sure that the method can resolve ellipses in various domains.

Keywords

Coordinate Noun Phrases, Named Entity Recognition, NP Ellipsis Resolution, Text Mining

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Kinam Park ¹

Affiliations
1 Creative Information and Computer Institute, Korea University, KR

Abstract

Background/Objectives: This paper proposes a potential query recommendation system based on the user search history so that information search system users can express their potential information needs in a query, and the information they want can be searched. Methods/Statistical Analysis: The proposed system used users’ search query to analyze the associative relationship with existing users’ search history, and extracted users’ potential information needs. The extracted potential information needs are recommended to users in the recommendation query. Findings: This paper used 27,656 pieces of search history data for analyzing the utility of the proposed system and conducted a behavioral experiment. The experiment found that the subjects showed a statistically higher level of satisfaction when using the proposed system than when using a general search engine. Improvements/Applications: In the future, it will be possible to secure the reliability of recommended queries by expanding and solidifying the search history through researches on personalization.

Keywords

Information Retrieval, Potential Knowledge, Query, Recommendation, Search Log.

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