Name
Abstract | ||
|---|---|---|
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information environments on-line in search of pages relevant to the user, by traversing hyperlinks in an autonomous and intelligent fashion. Each agent adapts to the spatial and temporal regularities of its local context thanks to a combination of machine learning techniques inspired by ecological models: evolutionary adaptation with local selection, reinforcement learning and selective query expansion by internalization of environmental signals, and optional relevance feedback. We evaluate the feasibility and performance of these methods in three domains: a general class of artificial graph environments, a controlled subset of the Web, and (preliminarly) the full Web. Our results suggest that InfoSpiders could take advantage of the starting points provided by search engines, based on global word statistics, and then use linkage topology to guide their search on-line. We show how this approach can complement the current state of the art, especially with respect to the scalability challenge. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1023/A:1007653114902 | Machine Learning - Special issue on information retrieval |
Keywords | Field | DocType |
InfoSpiders,distributed information retrieval,evolutionary algorithms,local selection,internalization,reinforcement learning,neural networks,relevance feedback,linkage topology,scalability,selective query expansion,adaptive on-line Web agents | World Wide Web,Relevance feedback,Evolutionary algorithm,Query expansion,Computer science,Artificial intelligence,Hyperlink,Adaptive algorithm,Artificial neural network,Machine learning,Reinforcement learning,Scalability | Journal |
Volume | Issue | ISSN |
39 | 2/3 | 0885-6125 |
Citations | PageRank | References |
87 | 11.51 | 32 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Filippo Menczer | 1 | 3874 | 268.67 |
| Richard K. Belew | 2 | 2047 | 865.82 |
| Jaime G. Carbonell | 3 | 5019 | 724.15 |
| Yiming Yang | 4 | 3299 | 344.91 |