Log in
Language:

MERAL Myanmar Education Research and Learning Portal

  • Top
  • Universities
  • Ranking
To
lat lon distance
To

Field does not validate



Index Link

Index Tree

Please input email address.

WEKO

One fine body…

WEKO

One fine body…

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}
  1. University of Information Technology
  2. Faculty of Information Science

Querying Connected Tuple Trees for Relational Keyword Search

http://hdl.handle.net/20.500.12678/0000005403
http://hdl.handle.net/20.500.12678/0000005403
3a96d956-9629-4afb-9ce2-0bd667cac9b0
7010d09e-675a-4115-a067-7590d45dc97a
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
Back
0
0
views
downloads
See details
Views Downloads

Versions

Ver.1 2020-09-16 09:50:36.632805
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Export

OAI-PMH
  • OAI-PMH DublinCore
Other Formats
  • JSON

Confirm


Back to MERAL


Back to MERAL