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A problem of multi-keyword search in a structured peer-to-peer (P2P) distributed computing system is considered. Methods have been developed to employ term-set indexing in a P2P system. Such an approach is an attempt to avoid excessive communication cost incurred by intersection operations in a single-term indexing
Query-by-keywords is the most popular manner to search for data in this computing age. However, most work was proposed for searching centralized relational databases. This paper investigates how keyword search is to be deployed in relational database-enabled peer-to-peer systems. Unlike centralized system, the key
(P2P) computing model has fueled the autonomous data sharing over the Internet in a more flexible fashion. Needless to say, XML data retrieval in P2P systems has become attractive to professionals in both research and industrial communities. In this paper, we propose a Bloom-Filter based keyword search framework for XML
ASEKS based on keyword spotting technology in the peer-to-peer (P2P) network. The indexing sub-model spots information in local audio files and generates indices for later query; and the P2P networks distributes the query and gathers the results. ASEKS supports scalability and avoids the bottleneck of network load that
Most educational resource grids are required to support multi-attribute multi-keyword fuzzy-matching queries. But such queries are not efficiently supported in current structured P2P systems. Towards an efficient P2P system capable of processing multi-attribute multi-keyword fuzzy-matching queries with high recall
Keyword search is an important aspect in p2p systems. Some key search methods for structured p2p systems use hypercube as a logic keyword search layer. However, the search is inefficient when query keyword set is small. In this paper, this weakness is addressed by replacing hypercube with a modified Cube-Connected
Recent research has shown that keyword search is a friendly and potentially effective way to retrieve information of interest over relational databases. Existing work has generally focused on implementing keyword search in centralized databases. This paper addresses keyword search over distributed databases. We adopts
Peer-to-peer approaches bring one perfect alternative for the Web content search. However, how to search and retrieve the data based on the content query is still an open problem for peer-to-peer systems. In this paper we propose History-based Multi-keywords Search(HMS) in unstructured peer-to-peer systems, which only
Efficient discovery of information based on partially specified and misspelled query keywords is a challenging problem in large scale peer-to-peer (P2P) networks. This paper presents QPM, a P2P search mechanism for efficient information retrieval with misspelled and partial keywords. QPM uses the double metaphone
In this paper we focus on building keyword search service over unstructured Peer-to-Peer (P2P) networks. Current state-of-the-art keyword search approaches for unstructured P2P systems are either blind or informed. Blind search methods such as flooding in Gnutella generate a large of redundant cloned messages and
The primary challenge in developing a peer-to- peer(P2P) file sharing system is implementing an efficient keyword search mechanism. Current keyword search approaches for structured P2P networks are built on the distributed inverted index by keywords. However, when executing multiple-attribute queries, they suffer from
. So this paper attempts to implement a commerce topic faced P2P search engine system for mobile devices using WAP protocol: MCTSE. MCTSE is built on the operating system of RedHat Linux AS3 Update4: it builds the topic characteristic keywords set using extendable iterative select keyword (EISK) algorithm, and based on
In this paper we focus on building a large scale keyword search service over structured peer-to-peer (P2P) networks. Current state-of-the-art keyword search approaches for structured P2P systems are based on inverted list intersection. However, the biggest challenge in those approaches is that when the indices are
DHT has been proposed in the literature as a general infrastructure for building large scale distributed system. While DHT supports exact key search inherently, several arguments against it contend that DHT cannot support the keyword search well, which is widely used in real systems. Through study of search logs from
design and prototype implementation of XSense, an architecture supporting metadata and query services for an underlying large scale dynamic P2P sensor network. We cluster sensor devices into manageable groupings to optimise the query process and automatically locate appropriate clusters based on keyword abstraction from
number of users with diverse characteristics and needs. Currently, many research projects or practical applications have emerged which only support single keyword search, and few of them support semantic retrieval. In this paper, we propose a model of ontology-based semantic information retrieval systems according to hybrid
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
Previously, we proposed efficient, scalable decentralized processing of SPARQL queries for an ad-hoc Semantic Web data sharing system and explored optimization techniques. However, it has proven to be difficult to measure the performance of the proposed query processing in a decentralized settings with existing tools. This is because assessments on SPARQL query performance were typically targeted...
Chord is a common circular P2P model with high routing efficiency and stable data inquiring. This paper proposes the Hot-Chord algorithm according to the fact that hot resources have occupied the majority of searching in the P2P system. Hot-Chord algorithm constructs an inner chord dynamically by using the nodes which hot resources is locating, to decrease the inquiring space; Nodes join or leave...
In structured peer-to-peer (P2P) overlay networks, similar documents are randomly distributed over peers with their data identifiers consistently hashed, which makes complex search challenging. Current state-of-the-art complex query approaches in structured P2P systems are mainly based on inverted list intersection. When the identifiers are distributed among peers, a complex query may involve many...
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