Name
Abstract | ||
|---|---|---|
With the increasing amount of information available in recent years, searching for the desired content is becoming a challenging task. In this work, a tool for searching abstracts submitted to scientific conferences is introduced. It not only searches abstracts by the given keyword(s) but also displays abstracts related to a single or multiple selection. It also displays highly relevant abstracts together with possible keywords to help users refine their search. Analysis of the conditional similarity algorithm proposed here has shown that it does provide better output compared to ordinary cosine similarity, as well as the list of possible keywords reflects results of latent topic analysis. An interface for storing and sorting selected abstracts for future review and/or printing is also provided. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s00521-010-0392-6 | Neural Computing and Applications |
Keywords | DocType | Volume |
challenging task,better output,multiple selection,increasing amount,conditional similarity algorithm,triplet similarity,future review,ordinary cosine similarity,related document,text data miningknowledge visualization � neuroinformaticsbipartite graphdimensionality reductiondocument similarity,recent year,possible keyword,latent topic analysis | Journal | 20 |
Issue | ISSN | Citations |
7 | 1433-3058 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shiro Usui | 1 | 775 | 198.35 |
| Nilton Liuji Kamiji | 2 | 5 | 2.07 |
| Tatsuki Taniguchi | 3 | 13 | 2.29 |
| Naonori Ueda | 4 | 1902 | 214.32 |