Finding and reminding: file organization from the desktop
ACM SIGCHI Bulletin
Lifestreams: an alternative to the desktop metaphor
Conference Companion on Human Factors in Computing Systems
Internet browsing and searching: user evaluations of category map and concept space techniques
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Presto: an experimental architecture for fluid interactive document spaces
ACM Transactions on Computer-Human Interaction (TOCHI)
MyLifeBits: fulfilling the Memex vision
Proceedings of the tenth ACM international conference on Multimedia
UMEA: translating interaction histories into project contexts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Stuff I've seen: a system for personal information retrieval and re-use
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Personal information management
CHI '04 Extended Abstracts on Human Factors in Computing Systems
Usage patterns of collaborative tagging systems
Journal of Information Science
Fast, flexible filtering with phlat
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
P2PDocTagger: content management through automated P2P collaborative tagging
Proceedings of the VLDB Endowment
Social event radar: a bilingual context mining and sentiment analysis summarization system
ACL '12 Proceedings of the ACL 2012 System Demonstrations
Hi-index | 12.05 |
The advent of internet has led to a significant growth in the amount of information available, resulting in information overload, i.e. individuals have too much information to make a decision. To resolve this problem, collaborative tagging systems form a categorization called folksonomy in order to organize web resources. A folksonomy aggregates the results of personal free tagging of information and objects to form a categorization structure that applies utilizes the collective intelligence of crowds. Folksonomy is more appropriate for organizing huge amounts of information on the Web than traditional taxonomies established by expert cataloguers. However, the attributes of collaborative tagging systems and their folksonomy make them impractical for organizing resources in personal environments. This work designs a desktop collaborative tagging (DCT) system that enables collaborative workers to tag their documents. This work proposes an application in patent analysis based on the DCT system. Folksonomy in DCT is built by aggregating personal tagging results, and is represented by a concept space. Concept spaces provide synonym control, tag recommendation and relevant search. Additionally, to protect privacy of authors and to decrease the transmission cost, relations between tagged and untagged documents are constructed by extracting document's features rather than adopting the full text. Experimental results reveal that the adoption rate of recommended tags for new documents increases by 10% after users have tagged five or six documents. Furthermore, DCT can recommend tags with higher adoption rates when given new documents with similar topics to previously tagged ones. The relevant search in DCT is observed to be superior to keyword search when adopting frequently used tags as queries. The average precision, recall, and F-measure of DCT are 12.12%, 23.08%, and 26.92% higher than those of keyword searching. DCT allows a multi-faceted categorization of resources for collaborative workers and recommends tags for categorizing resources to simplify categorization easier. Additionally, DCT system provides relevance searching, which is more effective than traditional keyword searching for searching personal resources.