Zhishi.links Results for OAEI 2011

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Zhishi.links Results for OAEI 2011
Zhishi.links Results for OAEI 2011
Bibliographical Metadata
Subject: Ontology Alignment
Year: 2011
Authors: Xing Niu, Shu Rong, Yunlong Zhang, Haofen Wang
Venue OM
Content Metadata
Problem: Link Discovery
Approach: No data available now.
Implementation: Zhishi.links
Evaluation: Accuracy Evaluation

Abstract

This report presents the results of Zhishi.links, a distributed instance matching system, for this year’s Ontology Alignment Evaluation Initiative (OAEI) campaign. We participate in Data Interlinking track (DI) of IM@OAEI2011. In this report, we briefly describe the architecture and matching strategies of Zhishi.links, followed by an analysis of the results.Property "Has abstract" (as page type) with input value "This report presents the results of Zhishi.links, a distributed instance matching system, for this year’s Ontology Alignment Evaluation Initiative (OAEI) campaign. We participate in Data Interlinking track (DI) of IM@OAEI2011. In this report, we briefly describe the architecture and matching strategies of Zhishi.links, followed by an analysis of the results." contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process.

Conclusion

In this report, we have presented a brief description of Zhishi.links, an instance matching system. We have introduced the architecture of our system and specific techniques we used. Also, the results have been analyzed in detail and several guides for improvements have been proposed.Property "Has conclusion" (as page type) with input value "In this report, we have presented a brief description of Zhishi.links, an instance matching system. We have introduced the architecture of our system and specific techniques we used. Also, the results have been analyzed in detail and several guides for improvements have been proposed." contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process.

Future work

We look forwards to build an instance matching system with better performance and higher stability in the future.

Approach

Positive Aspects: No data available now.

Negative Aspects: No data available now.

Limitations: No data available now.

Challenges: – When it comes with the problem of homonyms, instance matching systems should exploit as much information as possible to enhance the discriminability of their matchers. Currently, subject to the fact that most descriptions given by New York Times are written in natural language, the performance of our semantic similarity calculator are constrained. We are considering more tests carrying out on datasets in different styles and designing a more robust system. – In DI track, only three types of resources are involved. The special words in names, which are extracted as values of characteristic properties, are chosen manually. Some smarter strategies should be applied to accomplish this mission.Property "Has Challenges" (as page type) with input value "– When it comes with the problem of homonyms, instance matching systems should exploit as much information as possible to enhance the discriminability of their matchers. Currently, subject to the fact that most descriptions given by New York Times are written in natural language, the performance of our semantic similarity calculator are constrained. We are considering more tests carrying out on datasets in different styles and designing a more robust system.</br>– In DI track, only three types of resources are involved. The special words in names, which are extracted as values of characteristic properties, are chosen manually. Some smarter strategies should be applied to accomplish this mission." contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process.

Proposes Algorithm: No data available now.

Methodology: No data available now.

Requirements: No data available now.

Limitations: No data available now.

Implementations

Download-page: http://apex.sjtu.edu.cn/apex_wiki/Zhishi.links

Access API: No data available now.

Information Representation: No data available now.

Data Catalogue: {{{Catalogue}}}Property "Has DataCatalouge" (as page type) with input value "{{{Catalogue}}}" contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process.

Runs on OS: No data available now.

Vendor: No data available now.

Uses Framework: No data available now.

Has Documentation URL: No data available now.

Programming Language: No data available now.

Version: No data available now.

Platform: No data available now.

Toolbox: No data available now.

GUI: No

Research Problem

Subproblem of: No data available now.

RelatedProblem: No data available now.

Motivation: No data available now.

Evaluation

Experiment Setup: Tests were carried out on a Hadoop computer cluster. Each node has a quad-core Intel Core 2 processor (4M Cache, 2.66 GHz), 8GB memory. The number of reduce tasks was set to 50.

Evaluation Method : Utilize distributed MapReduce framework to adopt index-based pre-matching

Hypothesis: No data available now.

Description: No data available now.

Dimensions: Accuracy

Benchmark used: DBpedia, Freebase, GeoNames

Results: No data available now.