Near-Duplicate detection for online-shops owners: an FCA-Based approach

Authors:
Dmitry I. Ignatov;Andrey V. Konstantiov;Yana Chubis
Affiliations:
National Research University Higher School of Economics, Moscow, Russia;National Research University Higher School of Economics, Moscow, Russia;National Research University Higher School of Economics, Moscow, Russia
Venue:
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Year:
2013

Citing 5
Cited 0

Efficient mining of association rules using closed itemset lattices

Information Systems
Formal Concept Analysis: Mathematical Foundations

Formal Concept Analysis: Mathematical Foundations
Identifying and Filtering Near-Duplicate Documents

COM '00 Proceedings of the 11th Annual Symposium on Combinatorial Pattern Matching
Improved robustness of signature-based near-replica detection via lexicon randomization

Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Frequent Itemset Mining for Clustering Near Duplicate Web Documents

ICCS '09 Proceedings of the 17th International Conference on Conceptual Structures: Conceptual Structures: Leveraging Semantic Technologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

We proposed a prototype of near-duplicate detection system for web-shop owners. It's a typical situation for this online businesses to buy description of their goods from so-called copyrighters. Copyrighter can cheat from time to time and provide the owner with some almost identical descriptions for different items. In this paper we demonstrated how we can use FCA for fast clustering and revealing such duplicates in real online perfume shop's datasets.