Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
SimFusion: measuring similarity using unified relationship matrix
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 2006 international workshop on Mining software repositories
Contextual search and name disambiguation in email using graphs
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
TF-IDF uncovered: a study of theories and probabilities
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Finding business information by visualizing enterprise document activity
Proceedings of the International Conference on Advanced Visual Interfaces
Information Retrieval: Implementing and Evaluating Search Engines
Information Retrieval: Implementing and Evaluating Search Engines
ACM Transactions on Information Systems (TOIS)
Am I wasting my time organizing email?: a study of email refinding
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Integrating multiple contexts in real-time collaboration applications
Proceedings of the 3rd Workshop on Context-awareness in Retrieval and Recommendation
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Sharing information in communication sessions enhances end user collaboration. However, today with documents indexed on keywords and on meta-data such as author, date, title, etc., it is left to the user to bring the right information or documents for sharing in communication sessions. In enterprises, typically users search contents of communication units that surround the shared documents to get appropriate documents. Further, the results a user expects also depends on the current communication context such as the current conference call or current event they are attending. Real-time prediction of the documents needed for information sharing in communication applications would enhance collaboration by providing enterprise users with the right content at the right time. In this work, we present an algorithm for predicting relevant documents for an enterprise user in any context. We propose a novel context progression tree algorithm that can not only search relevant documents but also merges threads based on their similarity of topic of discussion. We prove search properties on these trees and present results from our implementation on users in a real enterprise deployment.