DiffPost: Filtering Non-relevant Content Based on Content Difference between Two Consecutive Blog Posts

Abstract

One of the important issues in blog search engines is to extract the cleaned text from blog post. In practice, this extraction process is confronted with many non-relevant contents in the original blog post, such as menu, banner, site description, etc, causing the ranking be less-effective. The problem is that these non-relevant contents are not encoded in a unified way but encoded in many different ways between blog sites. Thus, the commercial vendor of blog sites should consider tuning works such as making human-driven rules for eliminating these non-relevant contents for all blog sites. However, such tuning is a very inefficient process. Rather than this labor-intensive method, this paper first recognizes that many of these non-relevant contents are not changed between several consequent blog posts, and then proposes a simple and effective DiffPost algorithm to eliminate them based on content difference between two consequent blog posts in the same blog site. Experimental result in TREC blog track is remarkable, showing that the retrieval system using DiffPost makes an important performance improvement of about 10% MAP (Mean Average Precision) increase over that without DiffPost.KeywordsRetrieval PerformanceRelevant ContentRetrieval SpeedImprove Retrieval PerformanceLanguage Modeling ApproachThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.