ECIR
2010
Springer
13 years 8 months ago
2010
Springer
ECIR
2010
Springer
13 years 8 months ago
2010
Springer
We describe a P2P association rule mining descriptor enrichment approach that statistically significantly increases accuracy by greater than 15% over the non-enriched baseline. Unl...
ECIR
2010
Springer
13 years 8 months ago
2010
Springer
Abstract. Machine learning ranking methods are increasingly applied to ranking tasks in information retrieval (IR). However ranking tasks in IR often differ from standard ranking t...
ECIR
2010
Springer
13 years 8 months ago
2010
Springer
Abstract. Traditional retrieval models assume that query terms are independent and rank documents primarily based on various term weighting strategies including TF-IDF and document...
ECIR
2010
Springer
13 years 9 months ago
2010
Springer
Personal lifelog archives contain digital records captured from an individual’s daily life, e.g. emails, web pages downloaded and SMSs sent or received. While capturing this info...
ECIR
2010
Springer
13 years 9 months ago
2010
Springer
Without a well formulated and structured question, it can be very difficult and time consuming for physicians to identify appropriate resources and search for the best available ev...
ECIR
2010
Springer
13 years 11 months ago
2010
Springer
Web search engines are composed of a large set of search nodes and a broker machine that feeds them with queries. A location cache keeps minimal information in the broker to regist...
ECIR
2010
Springer
13 years 11 months ago
2010
Springer
In this work we compare different techniques to automatically find candidate web pages to substitute broken links. We extract information from the anchor text, the content of the p...
ECIR
2010
Springer
13 years 11 months ago
2010
Springer
Abstract. Many tasks (e.g., search and summarization) result in an ordered list of items. In order to evaluate such an ordered list of items, we need to compare it with an ideal or...
ECIR
2010
Springer
14 years 5 days ago
2010
Springer
A promising way to accelerate similarity search is semantic hashing which designs compact binary codes for a large number of documents so that semantically similar documents are ma...