Making large-scale support vector machine learning practical
Advances in kernel methods
Using web structure for classifying and describing web pages
Proceedings of the 11th international conference on World Wide Web
A Study of Approaches to Hypertext Categorization
Journal of Intelligent Information Systems
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Analysis of anchor text for web search
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Usage patterns of collaborative tagging systems
Journal of Information Science
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Can social bookmarking enhance search in the web?
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Authors vs. readers: a comparative study of document metadata and content in the www
Proceedings of the 2007 ACM symposium on Document engineering
Can social bookmarking improve web search?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Exploring social annotations for web document classification
Proceedings of the 2008 ACM symposium on Applied computing
Exploring social annotations for information retrieval
Proceedings of the 17th international conference on World Wide Web
The Metadata Triumvirate: Social Annotations, Anchor Texts and Search Queries
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
A call for social tagging datasets
ACM SIGWEB Newsletter
A social approach to authoring media annotations
Proceedings of the 10th ACM symposium on Document engineering
Exploiting tag and word correlations for improved webpage clustering
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Tags vs shelves: from social tagging to social classification
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Latent subject-centered modeling of collaborative tagging: An application in social search
ACM Transactions on Management Information Systems (TMIS)
Journal of Information Science
Reorganizing clouds: A study on tag clustering and evaluation
Expert Systems with Applications: An International Journal
Evaluating tag filtering techniques for web resource classification in folksonomies
Expert Systems with Applications: An International Journal
Analyzing tag distributions in folksonomies for resource classification
KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
Fuzzy combinations of criteria: an application to web page representation for clustering
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II
Learning user characteristics from social tagging behavior
Proceedings of the 23rd ACM conference on Hypertext and social media
Leveraging Social Bookmarks from Partially Tagged Corpus for Improved Web Page Clustering
ACM Transactions on Intelligent Systems and Technology (TIST)
Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies
Concurrency and Computation: Practice & Experience
Measuring website similarity using an entity-aware click graph
Proceedings of the 21st ACM international conference on Information and knowledge management
A self-adapted method for the categorization of social resources
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
User-generated annotations on social bookmarking sites can provide interesting and promising metadata for web document management tasks like web page classification. These user-generated annotations include diverse types of information, such as tags and comments. Nonetheless, each kind of annotation has a different nature and popularity level. In this work, we analyze and evaluate the usefulness of each of these social annotations to classify web pages over a taxonomy like that proposed by the Open Directory Project. We compare them separately to the content-based classification, and also combine the different types of data to augment performance. Our experiments show encouraging results with the use of social annotations for this purpose, and we found that combining these metadata with web page content improves even more the classifier's performance.