Orienteering in an information landscape: how information seekers get from here to there
INTERCHI '93 Proceedings of the INTERCHI '93 conference on Human factors in computing systems
Supporting collaborative learning during information searching
CSCL '95 The first international conference on Computer support for collaborative learning
The information-seeking practices of engineers: searching for documents as well as for people
Information Processing and Management: an International Journal
Collaborative information retrieval (CIR)
The New Review of Information Behaviour Research
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
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DAGSVM (Directed Acyclic Graph Support Vector Machines) has met with a significant success in information retrieval field, especially handling text classification tasks. This paper presents PDHCS (P2P-based Distributed Hypertext Categorization System) that classify hypertext in Peer-to-Peer networks. Distributed hypertext categorization can be easily implemented in PDHCS by combining the DAGSVM (Directed Acyclic Graph Support Vector Machines) learning architecture and Chord overlay network. Knowledge sharing among the distributed learning machines is achieved via utilizing both the special features of the DAG learning architecture and the advantages of support vector machines. The parallel structure of DAGSVM, the special features of support vector machines and decentralization of Chord overlay network lead to PDHCS being more efficient.