| D09-1014 | is an important first step in | data mining | applications . Earlier approaches |
| D10-1057 | context has been considered in | data mining | applications ( Muthukrishnan |
| D09-1113 | We use two approaches for click | data mining | , whose outputs are preference |
| D11-1049 | rules , which it has learned by | data mining | its knowledge base of beliefs |
| D09-1113 | determined by the methodology of click | data mining | approach . While it is possible |
| D14-1006 | see section 4.2 ) from the Weka | data mining | software ( Hall et al. , 2009 |
| D15-1193 | is a prerequisite for " CS 422 | Data mining | " . We get the prerequisite pairs |
| C00-1025 | touch on table extraction in text | data mining | . This paper l'ocuscs on mining |
| A00-1024 | 's Intelligent Miner suite for | data mining | . Since the point of this paper |
| D09-1113 | experimental results . 3.1 Click | data mining | We use two approaches for click |
| D10-1033 | the document before performing | data mining | ( Yi et al. , 2003 ) . Hence |
| C04-1027 | overgeneration is a well known problem of | data mining | algorithms and requires sound |
| D09-1028 | . The majority of geographical | data mining | frameworks utilize structured |
| D13-1060 | collected from the web via distributed | data mining | of parallel documents based on |
| acl-2001-inv1 | transcription system viable for audio | data mining | and other related applications |
| D08-1053 | alignment performance , web parallel | data mining | systems are able to acquire parallel |
| D09-1055 | , hence , we first introduce a | data mining | approach that is used to build |
| D14-1150 | ) and Knowledge Discovery and | Data Mining | ( KDD ) . Our choice for WWW |
| acl-2001-inv1 | near-term applications areas are audio | data mining | , selective dissemination of |
| D09-1096 | Witten and Eiba Frank . 2005 . | Data Mining | : Practical machine learning |
