نتایج جستجو برای: query log

تعداد نتایج: 134001  

2011
Shiau Hong Lim Peter Auer

We present theoretical results in terms of lower and upper bounds on the query complexity of noisy search with comparative feedback. In this search model, the noise in the feedback depends on the distance between query points and the search target. Consequently, the error probability in the feedback is not fixed but varies for the queries posed by the search algorithm. Our results show that a t...

2007
Mehdi Hosseini Hassan Abolhassani

Web query clustering is widely used by web information systems. In this paper we present a new content free method for web query log clustering. Query clustering has many applications including page ranking in web search, personalizing search result and web query expansion. In our approach, we first construct a bipartite graph for queries and visited URLs of a query log. Most of the clusters of...

Journal: :Algorithmica 2023

We present an algorithm to compute the geodesic $$L_1$$ farthest-point Voronoi diagram of m point sites in presence n rectangular obstacles plane. It takes $$O(nm+n \log + m\log m)$$ construction time using O(nm) space. This is first optimal for constructing obstacles. can construct a data structure same and space that answers farthest-neighbor query $$O(\log (n+m))$$ time.

2018
Eunjin Oh Hee-Kap Ahn

We study the point location problem on dynamic planar subdivisions that allows insertions and deletions of edges. In our problem, the underlying graph of a subdivision is not necessarily connected. We present a data structure of linear size for such a dynamic planar subdivision that supports sublinear-time update and polylogarithmic-time query. Precisely, the amortized update time is O( √ n log...

2000
Gerth Stølting Brodal Riko Jacob

The dynamic maintenance of the convex hull of a set of points in the plane is one of the most important problems in computational geometry. We present a data structure supporting point insertions in amortized O(log n · log log logn) time, point deletions in amortized O(log n · log logn) time, and various queries about the convex hull in optimal O(log n) worst-case time. The data structure requi...

1996
Lov K. Grover

Quantum search is a quantum mechanical technique for searching N possibilities in only √ N steps. This has been proved to be the best possible algorithm for the exhuastive search problem in the sense the number of queries it requires cannot be reduced. However, as this paper shows, the number of non-query operations, and thus the total number of operations, can be reduced. The number of non-que...

2009
Xing Yi Henry Feild James Allan

We propose a spelling correction algorithm that combines trusted domain knowledge and query log information for query spelling correction. This algorithm uses query reformulations in the query log and bigram language models built from queries for efficiently and effectively generating correction suggestions and ranking them to find valid corrections. Experimental results show that for both simp...

Journal: :CoRR 2013
Haitao Wang

We study the aggregate nearest neighbor searching for the Max operator in the plane. For a set P of n points and a query set Q of m points, the query asks for a point of P whose maximum distance to the points in Q is minimized. We present data structures for answering such queries for both L1 and L2 distance measures. Previously, only heuristic and approximation algorithms were given for both v...

2013
Di Jiang Kenneth Wai-Ting Leung Wilfred Ng Hao Li

Search engine query log is a valuable information source to analyze the users’ interests and preferences. In existing work, click graph is intensively utilized to analyze the information in query log. However, click graph is usually plagued by low information coverage, failure of capturing the diverse types of co-occurrence and the incapability of discovering the latent semantics in data. In th...

2016
Prahladh Harsha Rahul Jain Jaikumar Radhakrishnan

Let f : {0, 1} × {0, 1} → {0, 1} be a 2-party function. For every product distribution μ on {0, 1} × {0, 1}, we show that CCμ0.49(f) = O (( log prt1/8(f) · log log prt1/8(f) )2) , where CCε (f) is the distributional communication complexity of f with error at most ε under the distribution μ and prt1/8(f) is the partition bound of f , as defined by Jain and Klauck [Proc. 25th CCC, 2010]. We also...

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