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Keyword search is a user-friendly way to query XML data, such that users do not need to understand the complex syntax of structured query languages and the complex structural information of the underlying XML data. However, existing semantics suffer from limited expressiveness, thus users cannot obtain desired
propose a novel algorithm for keyword search in XML documents based on maximum repetitive unit. The basic idea of the algorithm is as follows. Firstly, extract the duplicate structures of XML documents as repetitive units. Then find out which units contain all the query keywords. The results returned are a number of
expressed in terms of keywords, over several XML streams. However, there are few algorithms that evaluate this kind of query. One of them is MKStream, which is the current state-of-the-art algorithm for processing keyword-based queries over XML streams. In order to improve scalability, in this paper we introduce PMKStream
Meaningful and useful return information is extraordinary important for information retrieval and XML keyword search. In this work, based on analysis the structure of XML document, we propose an algorithm to classify return matched nodes, we present formal analysis on LCA (lowest common ancestor) nodes ranking and LCA
In this paper, we study the problem of the data redundancy in XML Keyword Search by SLCA and propose a new mode to resolve it. We begin by introducing the notion of SLCA and analyzing its faults. Then we propose the concept of Indirect-SLCA (ISLCA) to reduce the redundancy basing on the notion of Heterogeneous node
At present many commercial database using Xpath and XQuery as XML retrieval standard, grammar about XPath and XQuery is complicated , it is difficult for general user to use. In this paper, the research work is focused on the keyword retrieval technology of XML document, designs a XML full-text information retrieval
Computing top-k results matching XML queries is gaining importance due to the increasing of large XML repositories. In this paper, we propose a novel two-layer-based index construction and associated algorithms for efficiently computing top-k results for SLCA-based XML keyword search. We have conducted expensive
An important facility to aid keyword search on XML data is suggesting alternative queries when user queries contain typographical errors. Query suggestion thus can improve users' search experience by avoiding returning empty result or results of poor qualities. In this paper, we study the problem of effectively and
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
Keyword search query processing is considered as the most promising way of information retrieval over XML data in present days as it relieves user from understanding complex schemas of XML document and writing difficult queries using XPath and XQuery. Till date various query processing techniques have been proposed to
Keyword search is a wildly popular way for querying XML document. However, the increasing volume of XML data poses new challenges to keyword search processing. Parallel database is an efficient solution for this problem. In this paper, we study the problem of effective keyword search for SLCA (Smallest lower common
Keywords can be used to query XML data without schema information. In this paper, a novel kind of query is proposed, top-k keyword search over XML streams. According to the set of keywords and the number of results, such query can retrieve the top-k XML data fragments most related to the keyword set. A novel ranking
With the XML becomes a de-facto standard for exchanging and presenting information, the study on XML keyword search has become the focus of information retrieval. Several recent studies have finished the effective XML keyword search, but not all approach is effective in identifying return information, not all search
Keyword-based search in relational database is an easy and effective way for ordinary users or Web users to access relational databases. Even though relational database management systems (RDBMs) have provided full-text search capabilities, they do not support keyword-based search model. The text databases and
Keyword search is considered to be an effective information discovery method for both structured and semi-structured data. In XML keyword search, query semantics is based on the concept of Lowest Common Ancestor (LCA). However, naive LCA-based semantics leads to exponential computation and result size. In the
There may exist a specific relationship between the keywords if an XML multi-keywords search has more than one answers. Such relationship can be speculated by SLCA. This paper proposes a user-friendly Top-k keywords searching approach based on the relationship of keywords. The SLCA of a keyword search is first
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
Along with the rapid growth of the xml data quantity on the Internet, the xml data retrieval research has attracted more and more attention. The searching algorithm based on key words is a research hotspot in this field. We present a context-based layered intersection scan algorithm (CLISA), which uses the context semantic of key words to filter large amount of redundant information, different from...
answers, such as short-answer questions, discussion questions etc. There are two factors that will affect the subjective item scoring: knowledge point and the nearness level. The unidirectional nearness algorithm in the fuzzy mathematics only focus on the keyword matching, but ignore the scoring of the knowledge point and
Keyword search for smallest lowest common ancestors (SLCAs) is a convenient method to retrieve information from XML documents for most of users, especially who have no knowledge or experience on XML. There have been many proposed algorithms solving SLCA problem through transforming XML documents into XML trees labeled
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