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(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
addresses the problem of keyword-based search in structured P2P networks. We propose a new keyword-based searching algorithm which can be implemented on top of any structured P2P overlay. We demonstrate that the proposed algorithm achieves very good searching results as it requires the minimum number of messages to be sent in
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
Traditionally, full text retrieval over structure peer- to-peer network has been implemented by inverted index by keywords. However, search based on this index scheme only support literally word match, not taking into account the meaning of words. In this paper, we present a new index scheme, inverted index by
Recently, peer-to-peer systems have become one of the most popular distributed applications. Many previous works have investigated identifier-based indexing systems that support a query-by-identifier service. However, clients usually have only partial information about an object, and prefer to query by keywords. In
This paper proposed a structured p2p model called balance-peer, introduce a method to partition the data rang without any global information on the load to. Our Balance-peer model is used to realize a partition-by-keyword indexing service based on DHT with each node in the system responsible for part of the keywords
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
In informal data sharing environments, misspellings cause problems for data indexing and retrieval. This is even more pronounced in mobile environments, in which devices with limited input devices are used. In a mobile environment, similarity search algorithms for finding misspelled data need to account for limited CPU and bandwidth. This demo shows P2P fast similarity search (P2PFastSS) running on...
In this paper, we propose CYBER, a CommunitY Based sEaRch engine, for information retrieval utilizing community feedback information in a DHT network. In CYBER, each user is associated with a set of user profiles that capture his/her interests. Likewise, a document is associated with a set of profiles-one for each indexed term. A document profile is updated by users who query on the term and consider...
following. First, the approximation of the superset relationship among keyword-sets by the descendance relationship among Bloom filters. Second, the use of a summary prefix tree (SPT), a trie indexing data structure, for keyword-based search over DHT. Third, an hybrid lookup procedure which exploits the sparsity of Bloom
important role to help communicate cloud computing system components. Tree based data structures are also used as index to perform the search faster. Currently most of the cloud providers use the keyword based search. Multi-attribute search optimizes the search process and also performs the search faster. The paper proposes a
In the past few years, videos become an ordinary communication mean for both personal and business activities. Not only the keyword search that have been utilized widely, but also the video content-based search, i.e. given a query video, the similar video sequences can be retrieved. Meanwhile, the increasing of the
Supporting complex and efficient lookup queries in peer-to-peer networks is challenging, though simple keyword based lookup queries are well supported by most deployed systems. This paper presents a two-level indexing structure built on distributed hash table (DHT) aiming to support range queries on high-dimensional
more uniformly across hosts. The results show that the data structure is capable of balancing resources, in particular when performing multiple keyword searches.
We present a simple yet novel technique for prefix search in P2P networks. The idea is to extract characters and their position information in a keyword to index objects. Our index scheme can achieve quite balanced loads, avoid hop-spots and single point of failure, reduce storage and maintenance costs, and offer some
indexed sequential searching, the system provides us with convenience of using the command like 'dir' of MS-DOS, and in general keyword searching, which is naturally impossible for the structured P2P systems, the searching speed is even faster than those of centralized P2P systems since a small list segment is scanned at
implement an indexing infrastructure supporting range queries on top of Distributed Hash Tables. The algorithm supports hierarchical keywords, and is especially designed for situations where a few keywords are very common while others are very uncommon. The design of our algorithm perfectly matches the requirements found in a
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