Name
Abstract | ||
|---|---|---|
It is important to find suitable partners in order to form successful collaborations between companies and university researchers. We consider finding the partners by calculating the similarity of the documents such as scientific papers and patents. We focus on weak (unique) links of researchers as the local similarity of their documents, instead of strong links as the global similarity of the documents. In the present paper, we propose a system that matches partners using documents such as research papers and patents. Given a query, the proposed system outputs a graph of unique research in retrieved documents. Each node in the graph corresponds to a word with a document frequency of two. Two words connected by an edge occur in the same two documents, and neither word appears in other retrieved documents. The edge is labeled with the names of the researchers involved in the documents in which the two words appear. Experiments are conducted using graphs output by the system. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/IIAI-AAI.2015.266 | IIAI-AAI |
Keywords | Field | DocType |
information retrieval,text mining,weak ties | Graph,World Wide Web,Information retrieval,Computer science,Interpersonal ties | Conference |
ISBN | Citations | PageRank |
978-1-4799-9957-6 | 0 | 0.34 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yasuhiro Yamada | 1 | 52 | 10.97 |
| Daisuke Ikeda | 2 | 28 | 3.36 |
| Sachio Hirokawa | 3 | 216 | 58.68 |