Titlebook: Database Systems for Advanced Applications; 18th International C Weiyi Meng,Ling Feng,Wei Song Conference proceedings 2013 Springer-Verlag

率直

Contemporary Photography as Collaborationen a greedy algorithm . is developed for expanding a community over time. Our results from extensive simulation on several real-world networks demonstrate that our Combine Model performs effectively and outperforms other algorithms.

先行

Contemporary Photography as Collaborationagrams (BDDs), and are suitable for implicitly handling large-scale combinatorial item set data. We present, in this paper, the algorithms for similarity joins between two data collections represented as ZDDs and pruning techniques. We also present the experimental results obtained by comparing thei

大量

Mathilde Bertrand,Karine Chambefort-Kay To this end, we propose the . scheduling strategy, which allows for selective data refreshing and integrates the benefits of SJF-based scheduling with an EDF-like policy. Our experiments demonstrate the effectiveness of our method, which does not only strike a fine trade-off between QoS and QoD but

addition

https://doi.org/10.1007/978-3-658-25253-3o the best of our knowledge, we are the first to propose a detailed, fast, and distributed .-ary AH-Tree index with allocation protocol, which has both theoretical and practical significance in this area.

抗原

Prime Ministerial Power and the Medias the clicking behavior explicitly and models the ternary relation between search queries, query terms and URLs. We evaluate the three proposed models against several strong baselines on a real-life query log. The experimental results show that the proposed models demonstrate significantly improved

受人支配

States in the international arbitral processQs accurately, we propose the Pattern-Concept-Time-Based (PCTB) method that utilizes query reformulation patterns, concepts behind the queries and the user’s continuous searching behavior to compute the similarity between two queries. To evaluate the effectiveness of our approach, we employ the AOL

易發(fā)怒

Can We Predict User Intents from Queries?n and recall) because of the following reasons:.(1) Queries for search engines are mostly limited to keywords or short natural language sentences, and.(2) Most search engines use traditional “keyword-in-document” information retrieval models..Obviously, a user’s search intent is not easily expressed

1FAWN

Finding Rising Stars in Social Networksthe beginning of their career but may become prominent contributors in the future. An effort for finding rising stars named PubRank is proposed, which considers mutual influence and static ranking of conferences or journals. In this work an improvement of PubRank is proposed by considering authors’

令人悲傷

連鎖,連串