MovieLens unplugged: experiences with an occasionally connected recommender system
Proceedings of the 8th international conference on Intelligent user interfaces
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Collaborative Filtering Using Weighted Majority Prediction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Collaborative filtering via gaussian probabilistic latent semantic analysis
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Retrieval evaluation with incomplete information
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
IEEE Transactions on Knowledge and Data Engineering
Automatic recognition of Chinese unknown words based on roles tagging
SIGHAN '02 Proceedings of the first SIGHAN workshop on Chinese language processing - Volume 18
The first international Chinese word segmentation Bakeoff
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
Chinese segmentation and new word detection using conditional random fields
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
The use of SVM for chinese new word identification
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Growing related words from seed via user behaviors: a re-ranking based approach
ACLstudent '10 Proceedings of the ACL 2010 Student Research Workshop
Chinese new word detection from query logs
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Why press backspace?: understanding user input behaviors in Chinese Pinyin input method
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
User Behaviors in Related Word Retrieval and New Word Detection: A Collaborative Perspective
ACM Transactions on Asian Language Information Processing (TALIP)
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In this paper, we proposed a novel method to detect new words in domain-specific fields based on user behaviors. First, we select the most representative words from domain-specific lexicon. Then combining with user behaviors, we try to discover the potential experts in this field who use those terminologies frequently. Finally, we make further efforts to identify new words from behaviors of those experts. Words used much more frequently in this community than others are most probably new words. In brief, our method follows a collaborative filtering way: first from words to find professional experts, then from experts to discover new words, which is different from the traditional new word detection methods. Our method achieves up to 0.86 in accuracy on a computer science related data set. Moreover, the proposed method can be easily extended to related words retrieval task. We compare our method with Google Sets and Bayesian Sets. Experiments show that our method and Bayesian Sets gives better results than Google Sets.