Browsing by Subject "Wikipedia"

Now showing 1 - 2 of 2

Open Access
Cluster labeling improvement by utilizing data fusion and Wikipedia
(2017-07) Ayduğan, Gökçe
A cluster is a set of related documents. Cluster labeling is the process of assigning descriptive labels to clusters. This study investigates several cluster labeling approaches and presents novel methods. The rst uses clusters themselves and extracts important terms, which distinguish clusters from each other, with different statistical feature selection methods. Then it applies di erent data fusion methods for combining their outcomes. Our results show that although it provides statistically signi cantly better results for some cases, it is not a stable and reliable labeling method. This can be explained by the fact that a good label may not occur in the cluster at all. The second exploits Wikipedia as an external resource and uses its anchor texts and categories to enrich the label pool. Labeling with Wikipedia anchor text fails because the suggested labels tend to focus on minor topics. Although the minor topics are related to the main topic, they do not exactly describe it. After this observation, we use categories of Wikipedia pages to improve our label pool in two ways. The rst fuses important terms and Wikipedia categories with rank based fusion methods. The second looks relatedness of Wikipedia pages to the clusters and use only categories of related pages. The experimental results show that both methods provide statistically signi - cantly better results than the other cluster labeling approaches that we examine in this study.
Open Access
Timestamp-based result cache invalidation for web search engines
(ACM, 2011) Alıcı, Sadiye; Altingovde I.S.; Özcan, Rıfat; Cambazoglu, B.B.; Ulusoy, Özgür
The result cache is a vital component for efficiency of large-scale web search engines, and maintaining the freshness of cached query results is the current research challenge. As a remedy to this problem, our work proposes a new mechanism to identify queries whose cached results are stale. The basic idea behind our mechanism is to maintain and compare generation time of query results with update times of posting lists and documents to decide on staleness of query results. The proposed technique is evaluated using a Wikipedia document collection with real update information and a real-life query log. We show that our technique has good prediction accuracy, relative to a baseline based on the time-to-live mechanism. Moreover, it is easy to implement and incurs less processing overhead on the system relative to a recently proposed, more sophisticated invalidation mechanism.