Confidence-Based incremental classification for objects with limited attributes in vertical search

Authors:
Ozer Ozdikis;Pinar Senkul;Siyamed Sinir
Affiliations:
Computer Engineering Department, Middle East Technical University, Ankara, Turkey;Computer Engineering Department, Middle East Technical University, Ankara, Turkey;Karniyarik Ltd., Ankara, Turkey
Venue:
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Year:
2012

Citing 13
Cited 0

Combining labeled and unlabeled data with co-training

COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
On integrating catalogs

Proceedings of the 10th international conference on World Wide Web
Machine Learning

Machine Learning
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval

ECML '98 Proceedings of the 10th European Conference on Machine Learning
Athena: Mining-Based Interactive Management of Text Database

EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
Evolving Extended Naive Bayes Classifiers

ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Raising the baseline for high-precision text classifiers

Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Iterative Bayes

Intelligent Data Analysis
A unified approach for schema matching, coreference and canonicalization

Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Improving the performance of focused web crawlers

Data & Knowledge Engineering
OfCourse: web content discovery, classification and information extraction for online course materials

Proceedings of the 18th ACM conference on Information and knowledge management
Web Crawling

Foundations and Trends in Information Retrieval
Sequential update of Bayesian network structure

UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

With vertical search engines, it is possible to search the web pages on a specific domain such as products, restaurants or academic papers and present the users only the interested information. Gathering and integrating such objects from multiple web pages into a single system provides a useful facility for users. Placing the extracted objects from multiple data sources into a single hierarchical structure is a challenging classification problem, especially if there are limited object attributes. In this work, we propose a confidence-based incremental Naïve Bayesian approach for categorization, focusing on the product domain. Incremental approach is based on extending the training set and retraining the classifier as new objects are assigned to a category with high confidence. The ordering of product data is taken into account as well. The proposed approach is applied on a vertical search engine that collects product data from several online stores.