Querying Connected Tuple Trees for Relational Keyword Search

Myint Myint Thein

MERAL Myanmar Education Research and Learning Portal

Index Tree

RootNode
- Co-operative College, Mandalay
- Cooperative College, Phaunggyi
- Co-operative University, Sagaing
- Co-operative University, Thanlyin
- Dagon University
- Kyaukse University
- Laquarware Technological college
- Mandalay Technological University
- Mandalay University of Distance Education
- Mandalay University of Foreign Languages
- Maubin University
- Mawlamyine University
- Meiktila University
- Mohnyin University
- Myanmar Institute of Information Technology
- Myanmar Maritime University
- National Management Degree College
- Naypyitaw State Academy
- Pathein University
- Sagaing University
- Sagaing University of Education
- Taunggyi University
- Technological University, Hmawbi
- Technological University (Kyaukse)
- Technological University Mandalay
- University of Computer Studies, Mandalay
- University of Computer Studies Maubin
- University of Computer Studies, Meikhtila
- University of Computer Studies Pathein
- University of Computer Studies, Taungoo
- University of Computer Studies, Yangon
- University of Dental Medicine Mandalay
- University of Dental Medicine, Yangon
- University of Information Technology
- University of Mandalay
- University of Medicine 1
- University of Medicine 2
- University of Medicine Mandalay
- University of Myitkyina
- University of Public Health, Yangon
- University of Veterinary Science
- University of Yangon
- West Yangon University
- Yadanabon University
- Yangon Technological University
- Yangon University of Distance Education
- Yangon University of Economics
- Yangon University of Education
- Yangon University of Foreign Languages
- Yezin Agricultural University
- New Index

Item

{"_buckets": {"deposit": "7010d09e-675a-4115-a067-7590d45dc97a"}, "_deposit": {"created_by": 45, "id": "5403", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "recid", "value": "5403"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/5403", "sets": ["user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Querying Connected Tuple Trees for Relational Keyword Search", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Keyword-based search in relational database is\nan easy and effective way for ordinary users or Web users\nto access relational database. Even though relational\ndatabase management systems (RDBMs) have provided fulltext\nsearch capabilities, they do not support keyword-based\nsearch model. The text databases and relational databases\nare different that is a challenging task to apply the keyword\nsearch techniques in information retrieval (IR) to DB. A\ncommon method to performing keyword search in\nrelational database is to generate the minimum connected\ntuple sets in schema graph transformed from relations.\nAlthough existing candidate network (CN) generation\nmethods retrieve a set of joining tuples, they are still\nproblem which is causing large overhead for CNs\ngeneration. In this paper, we propose a new candidate\nnetwork generation algorithm (Heuristic_CNGen) based on\nthe iterative deepening A* (IDA*) algorithm. The proposed\nalgorithm produces a minimum number of CNs according\nto the maximum number of tuple set. We generate CNs for a\ngiven keyword query. And then, we identify the connected\ntuple tree as a result according to generated CNs. We\nevaluate the proposed method on DBLP."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Keyword-based"}, {"interim": "Relational Database"}, {"interim": "Candidate Network"}, {"interim": "Connected Tuple Tree"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_no"}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "CAMP\u002712", "subitem_c_date": "13 March, 2012", "subitem_conference_title": "International Conference on Information Retrieval \u0026 Knowledge Management", "subitem_place": "Kuala Lumpur, Malaysia", "subitem_website": "https://ieeexplore.ieee.org/xpl/conhome/6200786/proceeding"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Myint Myint Thein"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Conference paper"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2012-03-13"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "10.1109/infrkm.2012.6204992"}, "item_title": "Querying Connected Tuple Trees for Relational Keyword Search", "item_type_id": "21", "owner": "45", "path": ["1596102391527"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000005403", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-09-16"}, "publish_date": "2020-09-16", "publish_status": "0", "recid": "5403", "relation": {}, "relation_version_is_last": true, "title": ["Querying Connected Tuple Trees for Relational Keyword Search"], "weko_shared_id": -1}

Querying Connected Tuple Trees for Relational Keyword Search

http://hdl.handle.net/20.500.12678/0000005403

Publication type
		Conference paper
Upload type
		Publication
Title
	Title	Querying Connected Tuple Trees for Relational Keyword Search
	Language	en
Publication date		2012-03-13
Authors
		Myint Myint Thein
Description
		Keyword-based search in relational database is an easy and effective way for ordinary users or Web users to access relational database. Even though relational database management systems (RDBMs) have provided fulltext search capabilities, they do not support keyword-based search model. The text databases and relational databases are different that is a challenging task to apply the keyword search techniques in information retrieval (IR) to DB. A common method to performing keyword search in relational database is to generate the minimum connected tuple sets in schema graph transformed from relations. Although existing candidate network (CN) generation methods retrieve a set of joining tuples, they are still problem which is causing large overhead for CNs generation. In this paper, we propose a new candidate network generation algorithm (Heuristic_CNGen) based on the iterative deepening A* (IDA*) algorithm. The proposed algorithm produces a minimum number of CNs according to the maximum number of tuple set. We generate CNs for a given keyword query. And then, we identify the connected tuple tree as a result according to generated CNs. We evaluate the proposed method on DBLP.
Keywords
		Keyword-based, Relational Database, Candidate Network, Connected Tuple Tree
Identifier		10.1109/infrkm.2012.6204992
Conference papers
		CAMP'12
		13 March, 2012
		International Conference on Information Retrieval & Knowledge Management
		Kuala Lumpur, Malaysia
		https://ieeexplore.ieee.org/xpl/conhome/6200786/proceeding