Partitioning sparse matrices with eigenvectors of graphs
SIAM Journal on Matrix Analysis and Applications
Fab: content-based, collaborative recommendation
Communications of the ACM
Efficient clustering of high-dimensional data sets with application to reference matching
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
The DBLP Computer Science Bibliography: Evolution, Research Issues, Perspectives
SPIRE 2002 Proceedings of the 9th International Symposium on String Processing and Information Retrieval
Clustering and Identifying Temporal Trends in Document Databases
ADL '00 Proceedings of the IEEE Advances in Digital Libraries 2000
Investigating the relationship between language model perplexity and IR precision-recall measures
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Email as spectroscopy: automated discovery of community structure within organizations
Communities and technologies
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
ICML '06 Proceedings of the 23rd international conference on Machine learning
Topics over time: a non-Markov continuous-time model of topical trends
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Eclipse Developer Contributions via Author-Topic Models
ICSEW '07 Proceedings of the 29th International Conference on Software Engineering Workshops
DBconnect: mining research community on DBLP data
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Recommendation over a Heterogeneous Social Network
WAIM '08 Proceedings of the 2008 The Ninth International Conference on Web-Age Information Management
Understanding research field evolving and trend with dynamic Bayesian networks
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Exploiting explicit semantics-based grouping for author interest finding
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Group topic modeling for academic knowledge discovery
Applied Intelligence
Mining Divergent Opinion Trust Networks through Latent Dirichlet Allocation
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Roles in social networks: Methodologies and research issues
Web Intelligence and Agent Systems
| Hi-index | 0.01 |
Conference Mining has been an important problem discussed these days for the purpose of academic recommendation. Previous approaches mined conferences by using network connectivity or by using semantics-based intrinsic structure of the words present between documents (modeling from document level (DL)), while ignored semantics-based intrinsic structure of the words present between conferences. In this paper, we address this problem by considering semantics-based intrinsic structure of the words present in conferences (richer semantics) by modeling from conference level (CL). We propose a generalized topic modeling approach based on Latent Dirichlet Allocation (LDA) named as Conference Mining (ConMin). By using it we can discover topically related conferences, conferences correlations and conferences temporal topic trends. Experimental results show that proposed approach significantly outperformed baseline approach in discovering topically related conferences and finding conferences correlations because of its ability to produce less sparse topics.