Guiding Queries to Information Sources with InfoBeacons

Cooper, Brian F.

doi:10.1007/978-3-540-30229-2_4

Cited by 15 publications

(18 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For each related cluster, the virtual peer computes the partial cosine similarity based on the retrieved scores. Then (lines [23][24][25][26][27][28][29][30][31], for the µ clusters with the highest partial cosine similarity, it sends its Bloom filter to the peer that holds the cluster's centroid (the cache peer), and retrieves the expected overlap size (cf. Eqn.…”

Section: Joining Peers In the Clustering-enhanced Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

PCIR: Combining DHTs and peer clusters for efficient full-text P2P indexing

Papapetrou¹,

Siberski²,

Nejdl³

2010

Computer Networks

View full text Add to dashboard Cite

Distributed hash tables (DHTs) are very efficient for querying based on key lookups. However, building huge term indexes, as required for IR-style keyword search, poses a scalability challenge for plain DHTs. Due to the large sizes of document term vocabularies, peers joining the network cause huge amounts of key inserts and, consequently, a large number of index maintenance messages. Thus, the key to exploiting DHTs for distributed information retrieval is to reduce index maintenance costs. Various approaches in this direction have been pursued, including the use of hybrid infrastructures, or changing the granularity of the inverted index to peer level. We show that indexing costs can be significantly reduced further by letting peers form groups in a self-organized fashion. Instead of each individual peer submitting index information separately, all peers of a group cooperate to publish the index updates to the DHT in batches. Our evaluation shows that this approach reduces index maintenance cost by an order of magnitude, while still keeping a complete and correct term index for query processing.

show abstract

Section: Joining Peers In the Clustering-enhanced Algorithmmentioning

confidence: 99%

“…To overcome these limitations, super peer topologies were proposed, where dedicated nodes take the responsibility for index maintenance and access [29,30]. While these systems scale better, they require peers with very good network connections and high availability to cope with the workload imposed by these tasks.…”

Section: P2p Information Retrievalmentioning

confidence: 99%

PCIR: Combining DHTs and peer clusters for efficient full-text P2P indexing

Papapetrou¹,

Siberski²,

Nejdl³

2010

Computer Networks

View full text Add to dashboard Cite

show abstract

“…Instead, we build a probabilistic overlay network for each query that occurs in the network. The approach that resembles our work most closely is the InfoBeacons system by Cooper [10], which is a middleware system designed for connecting uncooperative Web information sources by so-called beacons. Each beacon manages a small number of information sources and is in charge of sending user queries to appropriate sources.…”

Section: Query-pattern-based Approachesmentioning

confidence: 99%

Using taxonomies for content-based routing with ants

2007

View full text Add to dashboard Cite

Although the ant metaphor has been successfully applied to routing of data packets both in wireless and fixed networks, little is known yet about its appropriateness for search in peer-to-peer environments. This paper presents SemAnt, a distributed content-based routing algorithm based on the Ant Colony Optimization meta-heuristic and adapted for deployment in peer-to-peer networks. Under the assumption that content is annotated according to a taxonomy, it is possible to determine the hierarchical relationships between queries, and to exploit this information to improve the routing process. Our results show that using taxonomies enhances search performance in peer-to-peer networks. The degree of enhancement is highly dependent on the content distribution in the network.

show abstract

“…[5] proposes to maintain collection-wide information as well as routing tables at designated super-peers, called infobeacons. [2] collect query statistics at super-peers to facilitate efficient keyword query processing.…”

Section: Related Workmentioning

confidence: 99%

DHTs over Peer Clusters for Distributed Information Retrieval

Papapetrou

Siberski

Balke

et al. 2007

21st International Conference on Advanced Networking and Applications (AINA '07)

View full text Add to dashboard Cite

Distributed Hash Tables (DHTs) are very efficient for querying based on key lookups, if only a small number of keys has to be registered by each individual peer. However, building huge term indexes, as required for IR-style keyword search, are impractical with plain DHTs. Due to the large sizes of document term vocabularies, joining peers cause huge amounts of key inserts, and subsequently large numbers of index maintenance messages. Thus, the key to exploiting DHTs for distributed information retrieval is to reduce index maintenance. We show that this can be achieved by combining DHTs with peer clustering. Peers are first clustered into communities, each of the communities having a representative super-peer. Then all occurrences of a term in a community are published to the global DHT in a batch by the representative super-peer. Our evaluation shows that this reduces index maintenance cost by an order of magnitude, while still keeping a complete and correct term index for query processing.

show abstract

Guiding Queries to Information Sources with InfoBeacons

Cited by 15 publications

References 31 publications

PCIR: Combining DHTs and peer clusters for efficient full-text P2P indexing

PCIR: Combining DHTs and peer clusters for efficient full-text P2P indexing

Using taxonomies for content-based routing with ants

DHTs over Peer Clusters for Distributed Information Retrieval

Contact Info

Product

Resources

About