Cited By
View all- Nielsen FHansen L(2020)Creating Semantic RepresentationsStatistical Semantics10.1007/978-3-030-37250-7_2(11-31)Online publication date: 9-Jun-2020
Possible Confounds in Word-based Semantic Similarity Test Data
Authors: 
Malay Bhattacharyya, Yoshihiko Suhara, Md Mustafizur Rahman, 
Markus KrauseAuthors Info & Claims
Malay Bhattacharyya, Yoshihiko Suhara, Md Mustafizur Rahman, Markus KrauseAuthors Info & ClaimsPages 147 - 150
Abstract
Semantic similarity or semantic relatedness are features of natural language that contribute to the challenge machines face when analyzing text. Although semantic relatedness is still a complex challenge only few ground truth data set exist. We argue that the available corpora used to evaluate the performance of natural language tools do not capture all elements of the phenomenon. We present a set of simple interventions that illustrate 1) framing effects influence similarity perception, 2) the distribution of similarity across multiple users is important and 3) semantic relatedness is asymmetric.
References
[1]
Alexander Budanitsky and Graeme Hirst. 2001. Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures. In Proc. Workshop on WordNet and Other Lexical Resources.
[2]
Lev Finkelstein, Evgeniy Gabrilovich, Yossi Matias, Ehud Rivlin, Zach Solan, Gadi Wolfman, and Eytan Ruppin. 2002. Placing Search in Context: The Concept Revisited. ACM Transactions on Information Systems 20, 1 (2002).
[3]
Evgeniy Gabrilovich and Shaul Markovitch. 2007. Computing Semantic Relatedness using Wikipedia-based Explicit Semantic Analysis. In Proc. IJCAI '07. 1606--1611.
[4]
Jay J. Jiang and David W. Conrath. 1997. Semantic similarity based on corpus statistics and lexical taxonomy. arXiv cmp-lg/9709008 (1997).
[5]
Philip Resnik. 1995. Using information content to evaluate semantic similarity in a taxonomy. In Proc. IJCAI '95. 448--453.
[6]
Michael Strube and Simone Paolo Ponzetto. 2006. WikiRelate! Computing Semantic Relatedness Using Wikipedia. In Proc. AAAI '16. 1419--1424.
Index Terms
- Possible Confounds in Word-based Semantic Similarity Test Data
Recommendations
Evaluating semantic similarity and relatedness over the semantic grouping of clinical term pairs
Display Omitted Objective: develop a method to quantify the similarity and relatedness of biomedical and clinical term pairs.Semantic similarity and relatedness measures exploit information extrapolated from the Unified Medical Language System.Evaluates ...
Ontology-based approach for measuring semantic similarity
The challenge of measuring semantic similarity between words is to find a method that can simulate the thinking process of human. The use of computers to quantify and compare semantic similarities has become an important area of research in various ...
Research on Ontology-Based Measuring Semantic Similarity
ICICSE '08: Proceedings of the 2008 International Conference on Internet Computing in Science and EngineeringOntology is an explicit specification of a conceptualization on semantic and knowledge. This paper presents a formal definition on ontology and gives an example. Then, a method to measuring semantic similarity is presented. Semantic similarity is ...
Comments
Information & Contributors
Information
Published In
February 2017
472 pages
ISBN:9781450346887
DOI:10.1145/3022198
- General Chairs:
- Charlotte P. Lee,
- Steve Poltrock,
- Program Chairs:
- Louise Barkhuus,
- Marcos Borges,
- Wendy Kellogg
Copyright © 2017 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 25 February 2017
Check for updates
Author Tags
Qualifiers
- Poster
Conference
CSCW '17
Sponsor:
CSCW '17: Computer Supported Cooperative Work and Social Computing
February 25 - March 1, 2017
Oregon, Portland, USA
Acceptance Rates
CSCW '17 Companion Paper Acceptance Rate 183 of 530 submissions, 35%;
Overall Acceptance Rate 2,235 of 8,521 submissions, 26%
Upcoming Conference
CSCW '25
- Sponsor:
- sigchi
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 187Total Downloads
- Downloads (Last 12 months)3
- Downloads (Last 6 weeks)1
Reflects downloads up to 01 Jan 2025
Other Metrics
Citations
Cited By
View all- Nielsen FHansen L(2020)Creating Semantic RepresentationsStatistical Semantics10.1007/978-3-030-37250-7_2(11-31)Online publication date: 9-Jun-2020
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in