%0 Conference Paper %1 conf/ifip13/ThengTT10a %A Thein, Myint Myint %A Thwin, Mie Mie Su %B International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) %D 2012 %E Forbrig, Peter %E Paternò, Fabio %E Pejtersen, Annelise Mark %I Springer %K Candidate Connected Database Joining Keyword Network Query Relational Search Tree Tuple Tuples %N 6 %P 13-32 %R 10.5121/ijcseit.2012.2602 %T EFFICIENT SCHEMA BASED KEYWORD SEARCH IN RELATIONAL DATABASES %U http://airccse.org/journal/ijcseit/papers/2612ijcseit02.pdf %V 2 %X Keyword search in relational databases allows user to search information without knowing database schema and using structural query language (SQL). In this paper, we address the problem of generating and evaluating candidate networks. In candidate network generation, the overhead is caused by raising the number of joining tuples for the size of minimal candidate network. To reduce overhead, we propose candidate network generation algorithms to generate a minimum number of joining tuples according to the maximum number of tuple set. We first generate a set of joining tuples, candidate networks (CNs). It is difficult to obtain an optimal query processing plan during generating a number of joins. We also develop a dynamic CN evaluation algorithm (D_CNEval) to generate connected tuple trees (CTTs) by reducing the size of intermediate joining results. The performance evaluation of the proposed algorithms is conducted on IMDB and DBLP datasets and also compared with existing algorithms. %@ 978-3-642-15230-6

@inproceedings{conf/ifip13/ThengTT10a, abstract = {Keyword search in relational databases allows user to search information without knowing database schema and using structural query language (SQL). In this paper, we address the problem of generating and evaluating candidate networks. In candidate network generation, the overhead is caused by raising the number of joining tuples for the size of minimal candidate network. To reduce overhead, we propose candidate network generation algorithms to generate a minimum number of joining tuples according to the maximum number of tuple set. We first generate a set of joining tuples, candidate networks (CNs). It is difficult to obtain an optimal query processing plan during generating a number of joins. We also develop a dynamic CN evaluation algorithm (D_CNEval) to generate connected tuple trees (CTTs) by reducing the size of intermediate joining results. The performance evaluation of the proposed algorithms is conducted on IMDB and DBLP datasets and also compared with existing algorithms. }, added-at = {2018-04-05T08:43:02.000+0200}, author = {Thein, Myint Myint and Thwin, Mie Mie Su}, biburl = {https://www.bibsonomy.org/bibtex/2fef2878f3ebc95ee19a87363dfd8b26e/ijcseit}, booktitle = {International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)}, crossref = {conf/ifip13/2010}, doi = {10.5121/ijcseit.2012.2602}, editor = {Forbrig, Peter and Paternò, Fabio and Pejtersen, Annelise Mark}, ee = {https://doi.org/10.1007/978-3-642-15231-3_32}, interhash = {a5656ea5f4dd7432c6a1064b60bb1898}, intrahash = {fef2878f3ebc95ee19a87363dfd8b26e}, isbn = {978-3-642-15230-6}, issn = {2231-3117 [Online] ; 2231-3605 [Print]}, keywords = {Candidate Connected Database Joining Keyword Network Query Relational Search Tree Tuple Tuples}, language = {English}, month = dec, number = 6, pages = {13-32}, publisher = {Springer}, series = {IFIP Advances in Information and Communication Technology}, timestamp = {2018-04-05T08:43:02.000+0200}, title = {EFFICIENT SCHEMA BASED KEYWORD SEARCH IN RELATIONAL DATABASES}, url = {http://airccse.org/journal/ijcseit/papers/2612ijcseit02.pdf}, volume = 2, year = 2012 }