Name
Abstract | ||
|---|---|---|
In ranking algorithms for web graphs, such as PageRank and HITS, the lack of attention to concepts/topics representing web page content causes problems such as topic drift and mutually reinforcing relationships between hosts. This paper proposes a novel approach to expand the Web graph to incorporate conceptual information encoded by links (anchor text) between web pages. Using web graph link structure and conceptual information associated with each web page (automatically extracted from anchor text of inlinks), a new graph is defined where each node represents a unique pair of a web page and concept associated with that web page, and an edge represents an explicit or implicit link between two such nodes. This graph captures inter-concept relationships, which is then utilized by ranking algorithms. Our experimental results show that such an approach improves accuracy (e.g., first X precision) by retrieving links which are more authoritative given a user's context. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICDMW.2006.49 | ICDM Workshops |
Keywords | Field | DocType |
Web sites,graph theory,information retrieval,HITS,Minks,PageRank,Web graph link structure,Web page content,anchor text,concept-aware ranking,conceptual information encoded,implicit link,improves accuracy,retrieving links,user context | Static web page,Data mining,HITS algorithm,Web page,Computer science,Anchor text,Web modeling,Artificial intelligence,Information retrieval,Data Web,Web navigation,Backlink,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2702-7 | 4 | 0.47 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Colin DeLong | 1 | 21 | 2.59 |
| Sandeep Mane | 2 | 26 | 3.29 |
| Jaideep Srivastava | 3 | 5845 | 871.63 |