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.

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.

Foundation of Keyword Search in XML

2013 ◽  
pp. 1-16
Author(s):  
Weidong Yang ◽  
Hao Zhu
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Query Languages ◽  
Search Algorithms ◽  
The Other ◽  
Inverted Index ◽  
Xml Database ◽  
Xml Keyword Search ◽  
Lowest Common Ancestor ◽  
Structured Information

It has become desirable to provide a way of keyword search for users to query structured information in an XML database (data-centric retrieval) by combining database and information retrieval techniques. Therefore, the key challenges of keyword search in the XML database are how to define appropriate result models meeting user’s search intents, how to search the results by using efficient algorithms, and how to ranking the results. In this chapter, on one hand, the authors present the foundational knowledge of XML keyword search such as XML data models, XML query languages, inverted index, and Dewey encoding. On the other hand, some existing typical researches of keyword search in XML are presented, including the results models such as Smallest Lowest Common Ancestor (SLCA), Exclusive Lowest Common Ancestor (ELCA), Meaningful Lowest Common Ancestor (MLCA), the related search algorithms, and the ranking approaches.

scholarly journals XKFitler

2011 ◽  
Vol 1 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Weidong Yang ◽  
Fei Fang ◽  
Nan Li ◽  
Zhongyu (Joan) Lu
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Stream Processing ◽  
Query Languages ◽  
Information Discovery ◽  
Text Documents ◽  
Filter System ◽  
Lowest Common Ancestor ◽  
Xml Stream ◽  
User Friendly

Most existing XML stream processing systems adopt full structured query languages, such as XPath or XQuery, but they are difficult for ordinary users to learn and use. Keyword search is a user-friendly information discovery technique that has been extensively studied for text documents. This paper presents an XML stream filter system called XKFitler, which is the first system for supporting keyword search over XML stream. In XKFitler, the concepts of XLCA (eXclusive Lowest Common Ancestor) and XLCA Connecting Tree (XLCACT) are used to define the search semantic and results of keywords, and present an approach to filter XML stream according to keywords. The prototype XKFilter is implemented in the experiments.

XKFilter

2013 ◽  
pp. 1-18
Author(s):  
Weidong Yang ◽  
Fei Fang ◽  
Nan Li ◽  
Zhongyu (Joan) Lu
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Stream Processing ◽  
Query Languages ◽  
Information Discovery ◽  
Text Documents ◽  
Filter System ◽  
Lowest Common Ancestor ◽  
Xml Stream ◽  
User Friendly

Most existing XML stream processing systems adopt full structured query languages, such as XPath or XQuery, but they are difficult for ordinary users to learn and use. Keyword search is a user-friendly information discovery technique that has been extensively studied for text documents. This paper presents an XML stream filter system called XKFilter, which is the first system for supporting keyword search over XML stream. In XKFilter, the concepts of XLCA (eXclusive Lowest Common Ancestor) and XLCA Connecting Tree (XLCACT) are used to define the search semantic and results of keywords, and present an approach to filter XML stream according to keywords. The prototype XKFilter is implemented in the experiments.

XML keyword search algorithm based on efficient LCA

2010 ◽  
Vol 30 (3) ◽  
pp. 825-830
Author(s):  
Hong-hui ZHENG ◽  
Hong GUO
Keyword(s):  
Keyword Search ◽  
Search Algorithm ◽  
Xml Keyword Search

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.

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