scholarly journals MapReduce Implementation of an Improved Xml Keyword Search Algorithm

2018 ◽  
Vol 33 (2) ◽  
pp. 125-135
Author(s):  
Yong Zhang ◽  
Jing Cai ◽  
Quanlin Li
Keyword(s):  
Keyword Search ◽  
Search Algorithm ◽  
Xml Keyword Search

Research and Implementation of XML Keyword Search Algorithm Based on Semantic Relatives

2011 ◽  
Vol 267 ◽  
pp. 811-815
Author(s):  
Ming Yan Shen ◽  
Xin Li ◽  
Xiang Fu Meng
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Search Algorithm ◽  
Search Method ◽  
Document Structure ◽  
Xml Documents ◽  
Xml Keyword Search ◽  
Lowest Common Ancestor ◽  
Xml Document

The XML keyword search has been used widely in the application of XML documents. Most of the XML keyword search approaches are based on the LCA (lowest common ancestor) or its variants, which usually leads to the un-ideal recall and precision. This paper presents a novel XML keyword search method which based on semantic relatives. The method fully considers the semantic characteristics of the XML document structure. Based on the stack, the algorithm is also presented to merge the semantic relative nodes containing the keyword as the results of XML keyword search. The results of experiments have been identified the efficient and efficiency of our method.

XML Keyword Search Algorithm Based on Level-Traverse Encoding

2012 ◽  
Vol 263-266 ◽  
pp. 1553-1558
Author(s):  
Quan Zhu Yao ◽  
Bing Tian ◽  
Wang Yun He
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Search Algorithm ◽  
Bottom Up ◽  
Xml Documents ◽  
Xml Keyword Search ◽  
Lowest Common Ancestor ◽  
Definition Of ◽  
Labeling Method

For XML documents, existing keyword retrieval methods encode each node with Dewey encoding, comparing Dewey encodings part by part is necessary in LCA computation. When the depth of XML is large, lots of LCA computations will affect the performance of keyword search. In this paper we propose a novel labeling method called Level-TRaverse (LTR) encoding, combine with the definition of the result set based on Exclusive Lowest Common Ancestor (ELCA),design a query Bottom-Up Level Algorithm(BULA).The experiments demonstrate this method improves the efficiency and the veracity of XML keyword retrieval.

XDMA: A Dual Indexing and Mutual Summation Based Keyword Search Algorithm for XML Databases

2014 ◽  
Vol 24 (04) ◽  
pp. 591-615
Author(s):  
S. Selvaganesan ◽  
Su-Cheng Haw ◽  
Lay-Ki Soon
Keyword(s):  
Keyword Search ◽  
Search Algorithm ◽  
Ranking Problem ◽  
Xml Databases ◽  
Query Result ◽  
Novel Approach ◽  
Xml Keyword Search ◽  
Two Indices ◽  
Search Approach ◽  
Crucial Part

Achieving the effectiveness in relation to the relevance of query result is the most crucial part of XML keyword search. Developing an XML Keyword search approach which addresses the user search intention, keyword ambiguity problems and query/search result grading (ranking) problem is still challenging. In this paper, we propose a novel approach called XDMA for keyword search in XML databases that builds two indices to resolve these problems. Then, a keyword search technique based on two-level matching between two indices is presented. Further, by utilizing the logarithmic and probability functions, a terminology that defines the Mutual Score to find the desired T-typed node is put forward. We also introduce the similarity measure to retrieve the exact data through the selected T-typed node. In addition, grading for the query results having comparable relevance scores is employed. Finally, we demonstrate the effectiveness of our proposed approach, XDMA with a comprehensive experimental evaluation using the datasets of DBLP, WSU and eBay.

Adaptive Top-k Algorithm in SLCA-Based XML Keyword Search

2010 ◽  
Author(s):  
Hang Yu ◽  
Zhihong Deng ◽  
Yongqing Xiang ◽  
Ning Gao ◽  
Ming Zhang ◽  
...  
Keyword(s):  
Keyword Search ◽  
Xml Keyword Search
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