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KDD
2007
ACM
139views Data Mining» more  KDD 2007»
15 years 10 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
KDD
2007
ACM
189views Data Mining» more  KDD 2007»
15 years 10 months ago
Corroborate and learn facts from the web
The web contains lots of interesting factual information about entities, such as celebrities, movies or products. This paper describes a robust bootstrapping approach to corrobora...
Shubin Zhao, Jonathan Betz
87
Voted
KDD
2007
ACM
155views Data Mining» more  KDD 2007»
15 years 10 months ago
Mining templates from search result records of search engines
Metasearch engine, Comparison-shopping and Deep Web crawling applications need to extract search result records enwrapped in result pages returned from search engines in response ...
Hongkun Zhao, Weiyi Meng, Clement T. Yu
KDD
2007
ACM
210views Data Mining» more  KDD 2007»
15 years 3 months ago
Machine learning for stock selection
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
Robert J. Yan, Charles X. Ling
70
Voted
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
15 years 10 months ago
Partial example acquisition in cost-sensitive learning
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Victor S. Sheng, Charles X. Ling