Top K using Improved the XML Retrieval process of Structured and Unstructured Document
Abstract
XML Information retrieval is to verdict appropriate
documents to a users information need. XML are more pivot
on components of retrieve document of their information
needs with user needs. With the emergence of more XML
documents, effectively and easily retrieving information from
XML documents has become an active research area. In
recently years, day by day information increases and
formulates the short and ambivalent query of the users
normally. The information about the user stored in a user role.
The information is being stored in a semi-structured way, and
XML has standard as a standard for characterizing and
exchanging this type of data. Retrieval effectiveness of XML
search is higher, as a substitute of its ability due to show the
particular user parts. In this project we use XML retrieval
technique using top k. Here we use the top k approach using
threshold join algorithm. This approach fetches the results that
are close to the user’s query. The results from a user query
using an accumulation of structured document further
unstructured document to support the validity of our
approach.
Full Text:
PDFReferences
De Campos, L.M. ; Dept. de Cienc. de la Compute Intel.
Artificial, University; de Granada, Granada, Spain;
Fernandez Luna, J.M.; Huete, J.F.; Vicente-Lopez, E.,
“Using Personalization to Improve XML Retrieval”,
Knowledge and Data Engineering, IEEE Transactions
Volume: 26, Issue: 5, 13 May 2014, 1041-4347, 1280-
Zhen Hua Liu; Oracle Corp., Redwood Shores, CA,
USA; Ying Lu; Chang, H.J., “Efficient support of
XQuery Full Text in SQL/XML enabled RDBMS”, Data
Engineering (ICDE),2014 IEEE 30th International
Conference on March 31 2014-April 4 2014,1431-
,1132-1143.
L. M. de Campos, J. M. Fern andez -Luna, J. F. Huete,
and E. Vicente-L opez, XML search personalization
strategies usingquery expansion, reranking and a search
engine modification, in Proc. 28th ACM SAC, Coimbra,
Portugal, 2013, pp. 872877.
Nayana S. Zope, Ankita Kolhe, Prashant Bharambe,
“Ontology Based Information Retrieval Using Vector
Space Model”, International Journal Of Advanced
Research In Computer Science, 4 (10), Sept-Oct, 2013,
-214.
Meenakshi, S.; Dept. of Inf. Technol., Anna Univ.,
Chennai, India ; Senthilkumar, R., “Generating relevant
paths using keyword search on compact XML”, Recent
Trends in Information Technology (ICRTIT), 2013
International Conference on 25-27 July 2013 , 14399454
, 25-27 July 2013.
B. Steichen, H. Ashman, and V. Wade, “A comparative
survey of personalised information retrieval and adaptive
hypermedia techniques” Information Process
Management, vol. 48, no. 4, pp. 698724, 2012.
N. Matthijs and F. Radlinski, “Personalizing web search
using long term browsing history”, in Proc. 4th ACM
Int. Conf. Web Search Data Mining, Hong Kong, China,
, pp. 2534.
X. Tao, Y. Li, and N. Zhong, “A personalized ontology
model for web information gathering”, IEEE Trans.
Knowledge Data Eng., vol. 23, no. 4, pp. 496511, Apr.
Zhang Ji-Xin; Dept. of Inf. Sci. and Eng., Henan Univ. of
Technol., Zhengzhou, China; “Keyword Retrieval
Technology Research of XML Document”, Intelligent
Systems and Applications (ISA), 2011 3rd International
Workshop on 28-29 May 2011, 978-1-4244-9855-0, 1-3.
Akrivi Vlachou, Christos Doulkeridis, Yannis Kotidis,
jetil Nrvg, Vlachou, A. Dept. of Comput. Sci., NTNU,
Trondheim, Norway ; Doulkeridis, C. ; Kotidis, Y. ;
Norvag, K. , “Reverse top-k queries”, Data Engineering
(ICDE), 2010 IEEE 26th International Conference on 1-
March 2010 , 978-1-4244-5445-7 , 365-376.
Li, Guoliang ;Department of Computer Science and
Technology, Tsinghua University, Beijing 100084,
China; Feng, Jianhua ; Zhou, Lizhu, “Keyword searches
in data-centric XML documents using tree partitioning”,
Tsinghua Science and Technology (Volume:14 ,Issue: 1
), 17 January 2012 , 10.1016/S1007-0214(09)70002-1, 7-
D. Zeinalipour-Yazti et. al, “The Threshold Join
Algorithm for Top-k Queries in Distributed Sensor
Networks”, Proceedings of the 2nd international
workshop on Data management for sensor networks
DMSN (VLDB2005), Trondheim, Norway, ACM Press;
Vol. 96, 2005.
Consens, M.P.; Toronto Univ., Toronto ; Xin Gu ;
Kanza, Y.; Rizzolo, F. “Self Managing Top-k (Summary,
Keyword) Indexes in XML Retrieval”, Data Engineering
Workshop, 2007 IEEE 23rd International Conference on
-20 April 2007 , 978-1-4244-0832-0 , 245 252.
X. Tao, Y. Li, N. Zhong, “A personalized ontology
model for web information gathering”, IEEE Trans.
Knowl. Data Eng., vol. 23, no. 4, pp. 496-511, April
Lingli Li ;Harbin Inst. of Technol., Harbin ; Hongzhi
Wang ; Jianzhong Li ; Jizhou Luo, “Efficient Top-k
Keyword Search on XML Streams”, Young Computer
Scientists, 2008.
Ihab F. Ilyas, George Beskales, and Mohamed A.
Soliman, University of Waterloo, “A Survey of Top-k
Query Processing Techniques in Relational Database
Systems”, ACM Computing Surveys, Vol. 40, No. 4,
Article 11, Publication date: October 2008.
A. Marian, N. Bruno, , and L. Gravano, “Evaluating top
k queries over web-accessible databases”, ACM
Transactions on Database Systems (TODS), vol. 29, no.
, pp. 319-362, 2004.
N. Bruno, S. Chaudhuri, and L. Gravano, “Top-k
selection queries over relational databases: Mapping
strategies and performance evaluation”, ACM
Transactions on Database Systems (TODS), vol. 27, no.
, pp. 153-187, 2002.
K. Chang and S. won Hwang, “Minimal probing:
supporting expensive predicates for top-k queries”, in
Proceedings of the ACM International Conference on
Management of Data (SIGMOD), 2002, pp. 346-357.
C. Lang, Y.-C. Chang, and J. Smith, “Making the
threshold algorithm access cost aware”, IEEE
Transactions on Knowledge and Data Engineering, vol.
, no. 10, pp. 1297-1301, 2004.
Refbacks
- There are currently no refbacks.
Copyright © IJETT, International Journal on Emerging Trends in Technology