Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Retrieval and feedback models for blog feed search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Bloggers as experts: feed distillation using expert retrieval models
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Positional language models for information retrieval
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
An improved feedback approach using relevant local posts for blog feed retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Temporal models for microblogs
Proceedings of the 21st ACM international conference on Information and knowledge management
Cognitive temporal document priors
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Proceedings of the 24th ACM Conference on Hypertext and Social Media
The Impacts of Structural Difference and Temporality of Tweets on Retrieval Effectiveness
ACM Transactions on Information Systems (TOIS)
Improving pseudo-relevance feedback via tweet selection
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Using temporal bursts for query modeling
Information Retrieval
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This paper addresses blog feed retrieval where the goal is to retrieve the most relevant blog feeds for a given user query. Since the retrieval unit is a blog, as a collection of posts, performing relevance feedback techniques and selecting the most appropriate documents for query expansion becomes challenging. By assuming time as an effective parameter on the blog posts content, we propose a time-based query expansion method. In this method, we select terms for expansion using most relevant days for the query, as opposed to most relevant documents. This provide us with more trustable terms for expansion. Our preliminary experiments on Blog08 collection shows that this method can outperform state of the art relevance feedback methods in blog retrieval.