Link-Based Similarity Measures Using Reachability Vectors
We present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities tha...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/741608 |
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| _version_ | 1832550777994870784 |
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| author | Seok-Ho Yoon Ji-Soo Kim Jiwoon Ha Sang-Wook Kim Minsoo Ryu Ho-Jin Choi |
| author_facet | Seok-Ho Yoon Ji-Soo Kim Jiwoon Ha Sang-Wook Kim Minsoo Ryu Ho-Jin Choi |
| author_sort | Seok-Ho Yoon |
| collection | DOAJ |
| description | We present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities that does not suffer from these problems. In the proposed approach each target object is represented by a vector. Each element of the vector corresponds to all the objects in the given data, and the value of each element denotes the weight for the corresponding object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the “Random Walk with Restart” strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors. In this paper, we provide examples to show that our approach does not suffer from the aforementioned problems. We also evaluate the performance of the proposed methods in comparison with existing link-based measures, qualitatively and quantitatively, with respect to two kinds of data sets, scientific papers and Web documents. Our experimental results indicate that the proposed methods significantly outperform the existing measures. |
| format | Article |
| id | doaj-art-f015496c67fa4a1b81ecf9619ac2aee5 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-f015496c67fa4a1b81ecf9619ac2aee52025-02-03T06:05:53ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/741608741608Link-Based Similarity Measures Using Reachability VectorsSeok-Ho Yoon0Ji-Soo Kim1Jiwoon Ha2Sang-Wook Kim3Minsoo Ryu4Ho-Jin Choi5Department of Electronics and Computer Engineering, Hanyang University, Seoul 133-791, Republic of KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 133-791, Republic of KoreaDepartment of Computer and Software, Hanyang University, Seoul 133-791, Republic of KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 133-791, Republic of KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 133-791, Republic of KoreaDepartment of Computer Science, KAIST, Daejeon 305-701, Republic of KoreaWe present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities that does not suffer from these problems. In the proposed approach each target object is represented by a vector. Each element of the vector corresponds to all the objects in the given data, and the value of each element denotes the weight for the corresponding object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the “Random Walk with Restart” strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors. In this paper, we provide examples to show that our approach does not suffer from the aforementioned problems. We also evaluate the performance of the proposed methods in comparison with existing link-based measures, qualitatively and quantitatively, with respect to two kinds of data sets, scientific papers and Web documents. Our experimental results indicate that the proposed methods significantly outperform the existing measures.http://dx.doi.org/10.1155/2014/741608 |
| spellingShingle | Seok-Ho Yoon Ji-Soo Kim Jiwoon Ha Sang-Wook Kim Minsoo Ryu Ho-Jin Choi Link-Based Similarity Measures Using Reachability Vectors The Scientific World Journal |
| title | Link-Based Similarity Measures Using Reachability Vectors |
| title_full | Link-Based Similarity Measures Using Reachability Vectors |
| title_fullStr | Link-Based Similarity Measures Using Reachability Vectors |
| title_full_unstemmed | Link-Based Similarity Measures Using Reachability Vectors |
| title_short | Link-Based Similarity Measures Using Reachability Vectors |
| title_sort | link based similarity measures using reachability vectors |
| url | http://dx.doi.org/10.1155/2014/741608 |
| work_keys_str_mv | AT seokhoyoon linkbasedsimilaritymeasuresusingreachabilityvectors AT jisookim linkbasedsimilaritymeasuresusingreachabilityvectors AT jiwoonha linkbasedsimilaritymeasuresusingreachabilityvectors AT sangwookkim linkbasedsimilaritymeasuresusingreachabilityvectors AT minsooryu linkbasedsimilaritymeasuresusingreachabilityvectors AT hojinchoi linkbasedsimilaritymeasuresusingreachabilityvectors |