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SDM
2012
SIAM
235views Data Mining» more  SDM 2012»
11 years 7 months ago
Sampling Strategies to Evaluate the Performance of Unknown Predictors
The focus of this paper is on how to select a small sample of examples for labeling that can help us to evaluate many different classification models unknown at the time of sampl...
Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrech...
SIGIR
2012
ACM
11 years 7 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
ASUNAM
2011
IEEE
12 years 4 months ago
Is Objective Function the Silver Bullet? A Case Study of Community Detection Algorithms on Social Networks
Abstract—Community detection or cluster detection in networks is a well-studied, albeit hard, problem. Given the scale and complexity of modern day social networks, detecting “...
Yang Yang, Yizhou Sun, Saurav Pandit, Nitesh V. Ch...
ACL
2011
12 years 8 months ago
Neutralizing Linguistically Problematic Annotations in Unsupervised Dependency Parsing Evaluation
Dependency parsing is a central NLP task. In this paper we show that the common evaluation for unsupervised dependency parsing is highly sensitive to problematic annotations. We s...
Roy Schwartz, Omri Abend, Roi Reichart, Ari Rappop...
ICTIR
2009
Springer
13 years 2 months ago
An Analysis of NP-Completeness in Novelty and Diversity Ranking
Abstract. A useful ability for search engines is to be able to rank objects with novelty and diversity: the top k documents retrieved should cover possible interpretations of a que...
Ben Carterette
DEXAW
2010
IEEE
196views Database» more  DEXAW 2010»
13 years 4 months ago
Direct Optimization of Evaluation Measures in Learning to Rank Using Particle Swarm
— One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures ...
Ósscar Alejo, Juan M. Fernández-Luna...
ACL
2003
13 years 6 months ago
Evaluation Challenges in Large-Scale Document Summarization
We present a large-scale meta evaluation of eight evaluation measures for both single-document and multi-document summarizers. To this end we built a corpus consisting of (a) 100 ...
Dragomir R. Radev, Simone Teufel, Horacio Saggion,...
EACL
2006
ACL Anthology
13 years 6 months ago
CDER: Efficient MT Evaluation Using Block Movements
Most state-of-the-art evaluation measures for machine translation assign high costs to movements of word blocks. In many cases though such movements still result in correct or alm...
Gregor Leusch, Nicola Ueffing, Hermann Ney
IJCAI
2007
13 years 6 months ago
Constructing New and Better Evaluation Measures for Machine Learning
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
Jin Huang, Charles X. Ling
CLEF
2008
Springer
13 years 6 months ago
Overview of WebCLEF 2008
We describe the WebCLEF 2008 task. Similarly to the 2007 edition of WebCLEF, the 2008 edition implements a multilingual "information synthesis" task, where, for a given t...
Valentin Jijkoun, Maarten de Rijke