LearningPeerSelection: A Query Routing Approach for Information Retrieval in P2P Systems

In unstructured P2P systems, peers organize themselves into a random overlay. A challenging problem in these systems is to efficiently locate appropriate peers to answer a specific query. Recently, research works have focused on methods based on query history, which use the historical information of past queries and query hits to build a local knowledge base per peer. When a peer forwards a given query, it runs a learning algorithm that evaluates the query against the local knowledge base in order to select a set of relevant peers to whom the query will be routed. If the current peer fails to select a sufficient number of relevant peers it floods the query through the random overlay network, which badly affects the routing efficiency and effectiveness. To address the unsuccessful relevant peers search problem, we propose to organize the P2P network into semantic clusters of peers sharing similar knowledge bases. We implemented the proposed approach, and tested (i) its retrieval effectiveness in term of recall and precision, (ii) its routing efficiency in term of messages traffic. Experimental results show that our approach improves the recall and precision metrics while it dramatically reduce network traffic.

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“…We are also used the Learning Peer Selection algorithm proposed in [16] as a baseline. Hence, we compared the following routing methods :…”

Section: Methodsmentioning

confidence: 99%

“…Learning Peers Selection (LP S) [16] builds a knowledge base per peer by learning the implicit behavior of users that is deducted from query history. The knowledge base contains a set of user profiles.…”

Section: Rem In Dinmentioning

confidence: 99%

An Efficient Peer-to-Peer Semantic Overlay Network for Learning Query Routing

Yeferny¹,

Arour²,

Bouzeghoub³

2013

2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA)

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“…To test the efficiency of our approach, we used the Learning Peer Selection algorithm proposed in [7]. We defined two versions of this algorithm:…”

Section: Methodsmentioning

confidence: 99%

A Query Learning Routing Approach Based on Semantic Clusters

Yeferny¹

2011

IJAIT

Self Cite

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“…Our approach presents a solution for routing effectiveness of any learning routing approach. To test the efficiency of our approach, we used the Learning Peer Selection algorithm proposed in [7]. We defined two versions of this algorithm:…”

Section: Methodsmentioning

confidence: 99%

“…Learning Peers Selection (LPS) [7] learns the implicit behaviour of users that is deducted from query history. LPS supports a new knowledge or user profiles.…”

Section: Overview Of Query Routing In P2p Systemsmentioning

confidence: 99%

Untitled

2011

IJAIT

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Peer-to-peer systems have recently a remarkable success in the social, academic, and commercial communities. A fundamental problem in Peer-to-Peer systems is how to efficiently locate appropriate peers to answer a specific query (Query Routing Problem). A lot of approaches have been carried out to enhance search result quality as well as to reduce network overhead. Recently, researches focus on methods based on query-oriented routing indices. These methods utilize the historical information of past queries and query hits to build a local knowledge base per peer, which represents the user's interests or profile. When a peer forwards a given query, it evaluates the query against its local knowledge base in order to select a set of relevant peers to whom the query will be routed. Usually, an insufficient number of relevant peers is selected from the current peer's local knowledge base thus a broadcast search is investigated which badly affects the approach efficiency. To tackle this problem, we introduce a novel method that clusters peers having similar interests. It exploits not only the current peer's knowledge base but also that of the others in the cluster to extract relevant peers. We implemented the proposed approach, and tested (i) its retrieval effectiveness in terms of recall and precision, (ii) its search cost in terms of messages traffic and visited peers number. Experimental results show that our approach improves the recall and precision metrics while reducing dramatically messages traffic.

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LearningPeerSelection: A Query Routing Approach for Information Retrieval in P2P Systems

Cited by 10 publications

References 8 publications

An Efficient Peer-to-Peer Semantic Overlay Network for Learning Query Routing

An Efficient Peer-to-Peer Semantic Overlay Network for Learning Query Routing

A Query Learning Routing Approach Based on Semantic Clusters

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