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Cloud data owners prefer to outsource documents in an encrypted form for the purpose of privacy preserving. Therefore it is essential to develop efficient and reliable ciphertext search techniques. One challenge is that the relationship between documents will be normally concealed in the process of encryption, which will lead to significant search accuracy performance degradation. Also the volume...
The study on XML keyword search gradually becomes the focus of information retrieval. Most previous XML keyword search algorithms are based on SLCA (smallest lowest common ancestor), but in the process of keyword search, we discover that some weakness or flaw exists in SLCA, it is summarized as follows: (1) the query
XML filter approaches aim at XPath queries. However, many users tend to use keywords to describe requirements. SLCA (Smallest Lowest Common Ancestor)-based XML keyword search is one of the most important information retrieval approaches. Former approaches focus on building centralized index for a large scale of XML
TASTIER is a research project on the new information-access paradigm called type-ahead search, in which systems find answers to a keyword query on-the-fly as users type in the query. In this paper we study how to support fuzzy type-ahead search in TASTIER. Supporting fuzzy search is important when users have limited
There are currently two interface types for searching and browsing large image collections: keyword-based image retrieval (KBIR), and content-based image retrieval (CBIR). The KBIR system searches images according to the text of keyword annotated on images. This method is simple and relative effective to the query
disk I/O greatly. The optimal architecture of MPDBS is also derived by mathematical approach. Experimental results show that, given the same hardware configuration and TPC-H benchmark, comparing with Hive using Hadoop Distributed File System (HDFS), the query (i.e., statistical query, keyword query and point query
For most of the current search engines, the difference of their returned results are only because of the different keywords, i.e. for the same keywords used for searching, the same results will be returned. In fact, different users may have different search purposes even if they use the same keywords. In this paper
Peers search contents with information of contents such as keywords in many peer-to-peer contents sharing systems. In many peer-to-peer contents search architectures, queries are forwarded to peers which belong to clusters related with the keywords. Since clusters are basically constructed regardless of physical
Full-Text Retrieval. This system could find and locate the keywords which users interested in scientifically and efficiently. Besides the function of full-text retrieval, this system also contains ID Authentication, this ensures the safety of the share resources. In the end, we prove that our system is more efficient than
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