Name
Title | ||
|---|---|---|
Folksonomical P2p File Sharing Networks Using Vectorized Kansei Information As Search Tags |
Abstract | ||
|---|---|---|
We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web front the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their do product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown. through simulations. to be superior to or equal to the random-walk based one in terms of search speed. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1587/transinf.E92.D.2402 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
P2P file sharing, folksonomy, query forwarding, Kansei, human | Data mining,Similitude,Web search query,Peer-to-peer,Computer science,Kansei,Folksonomy,Dot product,File sharing,Shared resource | Journal |
Volume | Issue | ISSN |
E92D | 12 | 1745-1361 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kei Ohnishi | 1 | 39 | 17.71 |
| Kaori Yoshida | 2 | 40 | 8.46 |
| Yuji Oie | 3 | 378 | 68.37 |