NDLI: Blog feed search with a post index

Content Provider	Springer Nature Link
Author	Weerkamp, Wouter Balog, Krisztian Rijke, Maarten
Copyright Year	2011
Abstract	User generated content forms an important domain for mining knowledge. In this paper, we address the task of blog feed search: to find blogs that are principally devoted to a given topic, as opposed to blogs that merely happen to mention the topic in passing. The large number of blogs makes the blogosphere a challenging domain, both in terms of effectiveness and of storage and retrieval efficiency. We examine the effectiveness of an approach to blog feed search that is based on individual posts as indexing units (instead of full blogs). Working in the setting of a probabilistic language modeling approach to information retrieval, we model the blog feed search task by aggregating over a blogger’s posts to collect evidence of relevance to the topic and persistence of interest in the topic. This approach achieves state-of-the-art performance in terms of effectiveness. We then introduce a two-stage model where a pre-selection of candidate blogs is followed by a ranking step. The model integrates aggressive pruning techniques as well as very lean representations of the contents of blog posts, resulting in substantial gains in efficiency while maintaining effectiveness at a very competitive level.
Starting Page	515
Ending Page	545
Page Count	31
File Format	PDF
ISSN	13864564
Journal	Information Retrieval
Volume Number	14
Issue Number	5
e-ISSN	15737659
Language	English
Publisher	Springer Netherlands
Publisher Date	2011-03-15
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Blog feed search Post-level indexing Efficiency Generative language models Associations Pattern Recognition Data Structures, Cryptology and Information Theory Document Preparation and Text Processing Information Storage and Retrieval Data Mining and Knowledge Discovery
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems

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