WEIRD

Author:

Koll Matthew B.1

Affiliation:

1. Syracuse University, Syracuse, New York

Abstract

WEIRD is an automatic document retrieval system designed and implemented at Syracuse University, which attempts to advance the art of computerized retrieval from word-matching to judging conceptual similarity. WEIRD uses a vector space model to represent the relations among terms and documents. Items in the space are located according to their "meaning", which is their proximity to all other items in the data base as measured by co-occurrence frequencies. This is done without manipulating large matrices. The dimensions of the space are not used to define relations; items are defined solely by their position relative to the other items. Retrieval is determined by Euclidean distance from the plotted query. In the first section of the paper the basic characteristics of WEIRD are described. Second, the results of a preliminary evaluation are reported. Alternatives for further development of WEIRD are then considered.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Management Information Systems

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Word Embeddings: Reliability & Semantic Change;DISS ARTIF INTELL;2019

2. Information Retrieval using a Singular Value Decomposition Model of Latent Semantic Structure;ACM SIGIR Forum;2017-08-02

3. Document clustering using the LSI subspace signature model;Journal of the American Society for Information Science and Technology;2013-02-20

4. Indexing/Annotation;Logic and the Organization of Information;2012

5. Latent semantic analysis;Annual Review of Information Science and Technology;2005-09-22

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