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Graph Clustering for Keyword Search

Rose Catherine, S. Sudarshan
2009 International Conference on Management of Data  
In this paper, we address the issue of graph clustering for keyword search, using a technique based on random walks.  ...  Our performance metrics include edge compression, keyword search performance, and the time and space overheads for clustering.  ...  There are many other algorithms that are used for clustering, but which cannot be applied to the problem at hand, namely graph clustering for keyword search.  ... 
dblp:conf/comad/KS09 fatcat:sbt26qovmjdnxgwwot74mtxmbe

Query Suggestion and Recommendation Using Bipartite Graph and K-Means Clustering
IJARCCE - Computer and Communication Engineering

Dr. E.S. SAMUNDEESWARI, BRINDHA S
2014 IJARCCE  
., The proposed work carries out query suggestion and recommends query and URL"s using Bipartite graph and Kmeans clustering.  ...  KEYWORD WISE URL HIT COUNT Keyword wise URL cluster is a group of keywords used for visiting similar URLs.  ...  When the user is searching a new keyword for the same abbreviation, it is also added in the database.  ... 
doi:10.17148/ijarcce.2014.31137 fatcat:znxk3mwojjhnxb2qlibfa2imjq

Searching Keyword on Uncertain Graph Data by Using Enhanced Approach
English

Ashwini V. Urade, Pravin Kulurkar
2015 International Journal of Innovative Research in Computer and Communication Engineering  
Also o reduce processing time for keyword search in uncertain graph data.  ...  This technique provides effective result for searching keyword on graph. Uncertain graph is used in PPI network, modeling Road network, RDF data and social network etc.  ...  To overcome these issues, we propose a new technique for searching keyword on uncertain graph data. For this we use mining algorithm for creating sub-graph from uncertain graph. II.  ... 
doi:10.15680/ijircce.2015.0307015 fatcat:hgdgbde5d5bx3dmlray3ch5vhe

A Survey of Algorithms for Keyword Search on Graph Data [chapter]

Haixun Wang, Charu C. Aggarwal
2010 Managing and Mining Graph Data  
We first discuss keyword search methods for schema graphs. In Section 2 we focus on keyword search for XML data, and in Section 3, we focus on keyword search for relational data.  ...  In this survey, we discuss methods of keyword search on schema graphs, which are abstract representation for XML data and relational data, and methods of keyword search on schema-free graphs.  ...  Graph Exploration by Backward Search Many keyword search algorithms try to find trees embedded in the graph so that similar query semantics for keyword search over XML data can be used.  ... 
doi:10.1007/978-1-4419-6045-0_8 dblp:series/ads/WangA10 fatcat:7qain3m47vca5haasx5xxgzqwi

EMBANKS: Towards Disk Based Algorithms For Keyword-Search In Structured Databases [article]

Nitin Gupta
2011 arXiv   pre-print
Another such system is BANKS, which enables data and schema browsing together with keyword-based search for relational databases.  ...  We demonstrate that the cluster representation proposed in EMBANKS enables in-memory processing of very large database graphs.  ...  BANKS [BNH + 02] (acronym for Browsing ANd Keyword Searching) is a system that enables data and schema browsing together with keyword-based search for relational databases.  ... 
arXiv:1104.4384v1 fatcat:u4o62l3ningvvolfpmmr7nwx6i

Web Image Clustering with Reduced Keywords and Weighted Bipartite Spectral Graph Partitioning [chapter]

Su Ming Koh, Liang-Tien Chia
2006 Lecture Notes in Computer Science  
There has been recent work done in the area of search result organization for image retrieval. The main aim is to cluster the search results into semantically meaningful groups.  ...  In this paper we propose a two level reduced keywords approach for the bipartite spectral graph to reduce the complexity of bipartite spectral graph.  ...  The user might want to search for images which are related to the query in a specific sense semantically, such as to search for "Apple Computer" when querying "apple".  ... 
doi:10.1007/11922162_100 fatcat:rksjuzk5ojbzjcj6azb2xvk4qe

Test Model for Text Categorization and Text Summarization [article]

Khushboo Thakkar, Urmila Shrawankar
2013 arXiv   pre-print
This paper presents a model that uses text categorization and text summarization for searching a document based on user query.  ...  Document Summarization is an emerging technique for understanding the main purpose of any kind of documents.  ...  Information retrieval relies on the use of keywords to search for the desired information.  ... 
arXiv:1305.2831v1 fatcat:aqqmdgztyncc3o4ddjyhqrhxly

Hypergraph-based Wikipedia search with semantics

G. Sudha Sadasivam, K.G. Saranya, K.G. Karrthik
2013 International Journal of Web Science  
Further, clustering the articles within the graph structure based on the hypernyms narrows down the search  ...  A hypergraph structure is formed using hypernyms of the keywords to cluster the articles. Hypernyms extracted from the search query and keyword co-occurrences are used to extract relevant articles.  ...  The hypernyms for the keywords is then used to cluster the articles.  ... 
doi:10.1504/ijws.2013.056576 fatcat:7jxwxcf2zfhbljombepeiiwpfy

Keyword based search over semantic data in polynomial time

Paolo Cappellari, Roberto De Virgilio, Antonio Maccioni, Michele Miscione
2010 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010)  
In pursuing the development of Yanii, a novel keyword based search system on graph structures, in this paper we present the computational complexity study of the approach, highlighting a comparative study  ...  Search approach for data graph.  ...  Then, the second (sub-)goal is to search for a connection between such graph portions in order to build the most complete answers (or solutions) given the keywords.  ... 
doi:10.1109/icdew.2010.5452697 dblp:conf/icde/CappellariVMM10 fatcat:dyzmsncuf5abvn2v4prnuydkki

Exploiting Semantic Result Clustering to Support Keyword Search on Linked Data [chapter]

Ananya Dass, Cem Aksoy, Aggeliki Dimitriou, Dimitri Theodoratos
2014 Lecture Notes in Computer Science  
Keyword search is by far the most popular technique for searching linked data on the web.  ...  Our clustering hierarchy exploits graph patterns which are structured queries clustering together result graphs of the same structure and represent possible interpretations for the keyword query.  ...  In this paper, we present a novel approach for keyword search on RDF graph data. Our approach utilizes a semantic two-level hierarchical clustering of the keyword query results.  ... 
doi:10.1007/978-3-319-11749-2_34 fatcat:624uqzmqrfdrfn4spndtfvfbea

BLINKS

Hao He, Haixun Wang, Jun Yang, Philip S. Yu
2007 Proceedings of the 2007 ACM SIGMOD international conference on Management of data - SIGMOD '07  
To address these problems, we propose BLINKS, a bi-level indexing and query processing scheme for top-k keyword search on graphs.  ...  A top-k keyword search query on a graph nds the top k answers according to some ranking criteria, where each answer is a substructure of the graph containing all query keywords.  ...  Contributions To overcome these dif culties, we propose BLINKS (Bi-Level INdexing for Keyword Search), an indexing and query processing scheme for ranked keyword search over node-labeled directed graphs  ... 
doi:10.1145/1247480.1247516 dblp:conf/sigmod/HeWYY07 fatcat:cbrod677w5ex5mhiicfukakrxi

Yaanii: Effective Keyword Search over Semantic Dataset

Roberto De Virgilio, Paolo Cappellari, Michele Miscione
2010 Italian Information Retrieval Workshop  
It is based on a novel keyword search paradigm for graph-structured data, focusing in particular on the RDF data model.  ...  To this aim keywords search based systems are increasingly capturing the attention of researchers. In this paper, we present Yaanii 1 , a tool for the effective Keyword Search over semantic datasets.  ...  In [2] we proposed a novel approach to keyword search in the graph-structure data in a RDF representation.  ... 
dblp:conf/iir/VirgilioCM10 fatcat:zksg2surqzfb5cu7ktn7v5ilyy

Rank Based Clustering For Document Retrieval From Biomedical Databases [article]

Jayanthi Manicassamy, P. Dhavachelvan
2009 arXiv   pre-print
Apart from this graph tree construction is made for representing the level of relatedness of the documents that are networked together.  ...  The search engine has incorporated page ranking bases clustering concept which automatically represents relativeness on clustering bases.  ...  The main novelty lies in clustering the documents based on relativeness and representing in a graph tree structure for displaying documents.  ... 
arXiv:0912.2307v1 fatcat:kphaaco67bd7tpllwq4s2bp23e

KlusTree: Clustering Answer Trees from Keyword Search on Graphs [article]

Madhulika Mohanty, Maya Ramanath
2017 arXiv   pre-print
The problem of keyword search on graphs has been explored for over a decade now, but an important aspect that is not as extensively studied is that of user experience.  ...  Graph structured data on the web is now massive as well as diverse, ranging from social networks, web graphs to knowledge-bases.  ...  for the results of keyword search on a graph structured data.  ... 
arXiv:1705.09808v1 fatcat:zerrbzxvafhttfznpfsgjsytka

Hybrid Graph based Keyword Query Interpretation on RDF

Kaifeng Xu, Junquan Chen, Haofen Wang, Yong Yu
2010 International Semantic Web Conference  
Adopting keyword query interface to semantic search on RDF data can help users keep away from learning the SPARQL query syntax and understanding the complex and fast evolving data schema.  ...  The instance-based approaches relying on the original RDF graph can generate precise answers but take a long processing time.  ...  In the offline stage, a hybrid graph is constructed from the origin RDF graph. After that, a keyword index is built for the mapping of keywords to corresponding nodes in the hybrid graph.  ... 
dblp:conf/semweb/XuCWY10 fatcat:i4t252pksjevnf2l2wyvcojrim
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