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» Learning to rank for why-question answering
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ICML
2008
IEEE
15 years 10 months ago
Fast incremental proximity search in large graphs
In this paper we investigate two aspects of ranking problems on large graphs. First, we augment the deterministic pruning algorithm in Sarkar and Moore (2007) with sampling techni...
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash
66
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WWW
2003
ACM
15 years 10 months ago
Searching the workplace web
The social impact from the World Wide Web cannot be underestimated, but technologies used to build the Web are also revolutionizing the sharing of business and government informat...
Ronald Fagin, Ravi Kumar, Kevin S. McCurley, Jasmi...
VLDB
1990
ACM
116views Database» more  VLDB 1990»
15 years 1 months ago
A Probabilistic Framework for Vague Queries and Imprecise Information in Databases
A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
Norbert Fuhr
PVLDB
2008
131views more  PVLDB 2008»
14 years 9 months ago
Learning to create data-integrating queries
The number of potentially-related data resources available for querying -- databases, data warehouses, virtual integrated schemas -continues to grow rapidly. Perhaps no area has s...
Partha Pratim Talukdar, Marie Jacob, Muhammad Salm...
SAINT
2006
IEEE
15 years 3 months ago
MAAY: A Decentralized Personalized Search System
This paper focuses on decentralized personalized search engines. It is composed of three parts. Firstly, we formulate the problem and we propose a graph-based measure of quality o...
Frederic Dang Ngoc, Joaquín Keller, Gwendal...