Efficient semantic search on DHT overlays

Zhu, Yingwu; Hu, Yiming

doi:10.1016/j.jpdc.2007.01.005

Cited by 33 publications

(19 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…22 The concept used by ESS is to place indexes of semantically close files into same nodes with high probability of exploiting information retrieval algorithms and locality sensitive hashing. 23 A multiple keyword based searching technique called local indexing is used for locating resource using multiple keywords. 24 In this approach, the record of terms contained in each resource is stored on that particular node.…”

Section: Resource Discovery In Unstructured P2p Systemsmentioning

confidence: 99%

“…global indexing for instance in Ref. 23 In global indexing, the inverted list record is maintained on every node -information about nodes that contain a particular term. Upon query that contains multiple keywords, the query is routed to node containing that keyword.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

“…Moreover, communication cost grows with increase in length of inverted list. 24,23 In hybrid indexing, each node holds the complete inverted list of terms describing the resources on that node and also the inverted list of terms that are forwarding terms for resources shared on this node. Given a multiple keyword based query, the query is routed to node containing the search keywords.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

See 2 more Smart Citations

Local Semantic Indexing for Resource Discovery on Overlay Network Using Mobile Agents

Singh¹,

Cheng²,

Belavkin³

2014

IJCIS

View full text Add to dashboard Cite

One of the most crucial problems in a peer-to-peer system is locating of resources that are shared by various nodes. Various techniques suggested in literature suffer from drawbacks viz. saturation of network, inability to locate multikeyword based resource or locate resource based on semantics. We present the solution that is more efficient and effective for discovering shared resources on a network that is influenced by content shared by nodes. To reduce the search load on nodes that have uncorrelated content, an efficient migration route is proposed for mobile agent that is based on cosine similarity of content shared by nodes and user query and minimum support. Results show reduction in search load and traffic due to communication, and increase in locating of resources defined by multiple keys using mobile agent that are logically similar to user query. Furthermore, the results indicate that by use of our technique the relevance of search results is higher; that is obtained by minimal traffic generation/communication and hops made by mobile agent.

show abstract

Section: Resource Discovery In Unstructured P2p Systemsmentioning

confidence: 99%

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

See 1 more Smart Citation

Local Semantic Indexing for Resource Discovery on Overlay Network Using Mobile Agents

Singh¹,

Cheng²,

Belavkin³

2014

IJCIS

View full text Add to dashboard Cite

show abstract

“…But reference vectors are still chosen in a centralized fashion, which is not well suited for large datasets. Zhu and Hu (2007) generate the same index for semantically close files by using LSH and Vector Space Model (VSM), with the purpose of answering queries by only visiting a small number of nodes. But these hash values are directly used as resource keys, which destroy the load balance of Chord.…”

Section: Related Workmentioning

confidence: 99%

A scalable approach for content based image retrieval in cloud datacenter

Liao

Yang

et al. 2013

Inf Syst Front

View full text Add to dashboard Cite

The emergence of cloud datacenters enhances the capability of online data storage. Since massive data is stored in datacenters, it is necessary to effectively locate and access interest data in such a distributed system. However, traditional search techniques only allow users to search images over exact-match keywords through a centralized index. These techniques cannot satisfy the requirements of content based image retrieval (CBIR). In this paper, we propose a scalable image retrieval framework which can efficiently support content similarity search and semantic search in the distributed environment. Its key idea is to integrate image feature vectors into distributed hash tables (DHTs) by exploiting the property of locality sensitive hashing (LSH). Thus, images with similar content are most likely gathered into the same node without the knowledge of any global information. For searching semantically close images, the relevance feedback is adopted in our system to overcome the gap between low-level features and high-level features. We show that our approach yields high recall rate with good load balance and only requires a few number of hops.

show abstract

“…• Zhu et al [29] have proposed an approach to conduct efficient semantic search on DHT overlays. Their basic idea was to place indexes of semantically close files into the same peer nodes with high probability by adding major components on top of a DHT: extractor registry and semantic indexing and locating utility.…”

Section: Context and Related Workmentioning

confidence: 99%

A P2P Platform for Collaborative Aggregated Multimedia Sharing

Fakhfakh¹,

Zhang²,

Girod-Genet³

2013

View full text Add to dashboard Cite

Peer-to-peer technologies have emerged as a powerful and scalable communication model for large scale content sharing. However, they are not yet provided with optimized heterogeneous aggregated content management functionality since they lack rich semantic specifications. To overcome these shortcomings, we elaborated a reference model of P2P architecture for a dynamic aggregation, sharing and retrieval of heterogeneous multimedia contents (simple or aggregated). This architecture was mainly developed under the CAM4Home European research project and is fully based on the CAM4Home semantic metadata model. This semantic model relies on RDF (Resource Description Framework) and is rich (but simple enough), extensible and dedicated for the description of any kind of multimedia content. In this paper, we detail and evaluate an original semantic-based community network architecture for heterogeneous multimedia content sharing and retrieval. Within the presented architecture, multimedia contents are managed according to their associated CAM4Home semantic metadata through a structured P2P topology. This topology relies on a semantically enhanced DHT (Distributed Hash Table) and is also provided with an additional indexing system for offering semantic storage and search facilities and overcoming the problem of exact match keywords in DHTs.

show abstract

Efficient semantic search on DHT overlays

Cited by 33 publications

References 21 publications

Local Semantic Indexing for Resource Discovery on Overlay Network Using Mobile Agents

Local Semantic Indexing for Resource Discovery on Overlay Network Using Mobile Agents

A scalable approach for content based image retrieval in cloud datacenter

A P2P Platform for Collaborative Aggregated Multimedia Sharing

Contact Info

Product

Resources

About