Journal
SIGMOD'15: PROCEEDINGS OF THE 2015 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA
Volume -, Issue -, Pages 347-362Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2723372.2749451
Keywords
text stream; diversification; publish/subscribe
Categories
Funding
- Singapore MOE AcRF Tier 2 Grant [ARC30/12]
- Microsoft Research
Ask authors/readers for more resources
Massive amount of text data are being generated by a huge number of web users at an unprecedented scale. These data cover a wide range of topics. Users are interested in receiving a few up-to-date representative documents (e.g., tweets) that can provide them with a wide coverage of different aspects of their query topics. To address the problem, we consider the Diversity-Aware Top k Subscription (DAS) query. Given a DAS query, we continuously maintain an up-to-date result set that contains k most recently returned documents over a text stream for the query. The DAS query takes into account text relevance, document recency, and result diversity. We propose a novel solution to efficiently processing a large number of DAS queries over a stream of documents. We demonstrate the efficiency of our approach on real world dataset and the experimental results show that our solution is able to achieve a reduction of the processing time by 60-75% compared with two baselines. We also study the effectiveness of the DAS query.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available