The 31st Annual International ACM SIGIR Conference
20-24 July 2008, Singapore

Full Papers

A Boosting Algorithm for Learning Bipartite Ranking Functions with Partially Labeled Data
M. Amini, V. Truong and C. Goutte  (National Research Council Canada/LIP6)

Affective Feedback: An Investigation into the Role of Emotions in the Information Seeking Process
I. Arapakis J. M. Jose, and P. D. Gray  (University of Glasgow)

Evaluation Over Thousands of Queries
B. Carterette, V. Pavlu, E. Kanoulas, J. Allan, and J. A. Aslam  (University of Massachusetts Amherst/Northeastern University)

Personalized Active Learning for Collaborative Filtering
H. Abhay and Y. Yang  (Carnegie Mellon University)

The Good and the Bad System: Does the Test Collection Predict Users’ Effectiveness?
A. Al-Maskari, M. Sanderson and P. Clough  (University of Sheffield)

A Few Examples Go A Long Way: Constructing Query Models from Elaborate Query Formulations
K. Balog, W. Weerkamp and M. de Rijke  (University of Amsterdam)

Discovering Key Concepts in Verbose Queries
M. Bendersky and B. Croft  ( University of Massachusetts)

Query Expansion Using Gaze-Based Feedback on the Subdocument Level
G. Buscher, A. Dengel and L. van Elst  (DFKI)

Relevance Assessment: Are Judges Exchangeable and Does it Matter
P. Bailey, N. Craswell, I. Soboroff, P. Thomas, A. de Vries and E. Yilmaz  (NIST/Northeastern University/Microsoft/CWI/CSIRO ICT Centre)

A Lattice-Based Approach to Query-by-Example Spoken Document Retrieval
T.K. Chia, K.C. Sim, H. Li and H.T. Ng  (Institute for Infocomm Research/National University of Singapore)

Finding Question-Answer Pairs from Online Forums
G. Cong, L. Wang, C.Y. Lin, Y.I. Song and Y. Sun  (Aalborg University/Tianjin University/Microsoft Research Asia/Korea University)

Novelty and Diversity in Information Retrieval Evaluation
C. Clarke, M. Kolla, G. Cormack, O. Vechtomova, A. Ashkan, S. Büttcher, and I. MacKinnon  (University of Waterloo)

Selecting Good Expansion Terms for Pseudo-Relevance Feedback
G. Cao, J.Y. Nie, J. Gao and S. Robertson  (Microsoft Research/University of Montreal)

TSCAN: A Novel Method for Topic Summarization and Content Anatomy
C.C. Chen and M.C. Chen  (Academia Sinica/National Taiwan University)

A User Browsing Model to Predict Search Engine Click Data from Past Observations.
G. Dupret and B. Piwowarski  (Yahoo! Research Latin America)

Asymmetric Distance Estimation with Sketches for Similarity Search in High-Dimensional Spaces
W. Dong, M. Charikar and K. Li (Princeton University)

Learning from Labeled Features using Generalized Expectation Criteria
G. Druck, G. Mann and A. McCallum  (University of Massachusetts Amherst)

Learning to Rank with Partially-Labeled Data
K. Duh and K. Kirchhoff  (University of Washington)

Retrieval and Feedback Models for Blog Feed Search
J. Elsas, J. Arguello, J. Callan and J. Carbonell  (Carnegie Mellon University)

A Unified and Discriminative Model for Query Refinement
J. Guo, G. Xu, H. Li andX. Cheng  (Microsoft Research Asia/Information Security Center, ICT)

Learning to Rank with SoftRank and Gaussian Processes
J. Guiver and E. Snelson  (Microsoft Research)

Query Dependent Ranking Using K-Nearest Neighbor
X. Geng, T.Y. Liu, T. Qin, A. Arnold, H. Li and H.Y. Shum  (Institue of Computing Technology, Chinese Academy of Sciences/Microsoft Research Asia/Tsinghua University/ Carnegie Mellon University)

Comments-Oriented Document Summarization: Understanding Documents with Readers’ Feedback
M. Hu, A. Sun and E.P. Lim  (Nanyang Technological University)

Enhancing Text Clustering by Leveraging Wikipedia Semantics
J. Hu, L. Fang, Y. Cao, H. J. Zeng, H. Li, Q. Yang, and Z. Chen  (Microsoft Research Asia/Fudan University/Shanghai Jiao Tong Univeristy/ Hong Kong University of Science & Technology)

Retrieval Sensitivity Under Training Using Different Measures
B. He, C. Macdonald and I. Ounis  (University of Glasgow)

Social Tag Prediction
P. Heymann, D. Ramage and H. Garcia-Molina  (Stanford University)

Crosslingual Location Search
T. Joshi, J. Joy, T. Kellner, U. Khurana, A. Kumaran and V. Sengar  (Microsoft Research India)

Directly Optimizing Evaluation Measures in Learning to Rank
J. Xu, T.Y. Liu, M. Lu, H. Li, and W.Y. Ma (Microsoft Research Asia)

Optimizing Relevance and Revenue in Ad Search: A Query Substitution Approach
F. Radlinski, A. Broder, P. Ciccolo, E. Gabrilovich,  V. Josifovski and L. Riedel (Yahoo! Research/Cornell University)

A rank-aggregation approach to searching for optimal query-specific clusters
O. Kurland and C. Domshlak  (Technion)

Effective and Efficient User Interaction for Long Queries
G. Kumaran and J. Allan  (University of Massachusetts Amherst)

Intuition-Supporting Visualization of User’s Performance Based on Explicit Negative Higher-Order Relevance
H. Keskustalo, K. Jarvelin, A. Pirkola and J. Kekalainen  (University of Tampere)

The opposite of smoothing: A language model approach to ranking query-specific document clusters
O. Kurland  (Technion)

A Cluster-Based Resampling Method for Pseudo-Relevance Feedback
K.S. Lee, B. Croft and J. Allan  (University of Massachusetts Amherst/Chonbuk National University)

BrowseRank: Letting Web Users Vote for Page Importance
Y. Liu, B. Gao, T.Y. Liu, Y. Zhang, Z. Ma, S. He and H. Li  (Microsoft Research Asia)

EigenRank: A Ranking-Oriented Approach to Collaborative Filtering
N. Liu and Q. Yang  (Hong Kong University of Science & Technology)

How Do Users Find Things with PubMed?  Towards Automatic Utility Evaluation with User Simulations
J. Lin and M. Smucker  (University of Maryland/University of Massachusetts, Amherst)

Knowledge Transformation from Word Space to Document Space
T. Li, C. Ding, Y. Zhang and B. Shao  (Florida International University/University of Texas at Arlington)

Learning Query Intent from Regularized Click Graphs
X. Li, Y. Y. Wang and A. Acero  (Microsoft Research)

On Iterative Intelligent Medical Search
G. Luo and C. Tang  (IBM T.J. Watson Research Center)

Predicting Information Seeker Satisfaction in Community Question Answering
Y. Liu, J. Bian and E. Agichtein  (Emory University/Georgia Institue of Technology)

Reorganizing Compressed Text
N. R. Brisaboa, A. Fariña S. Ladra and G. Navarro  (University of Chile/University of A Coruña)

Spectral Geometry for Simultaneously Clustering and Ranking Query Search Results
Y. Liu, W. Li, Y. Lin and L. Jing  (The University of Texas at Dallas)

A Generation Model to Unify Topic Relevance and Lexicon-based Sentiment for Opinion Retrieval
M. Zhang and X. Ye  (Tsinghua University)

Attack Resistant Collaborative Filtering
B. Mehta and W. Nejdl  (Google Inc./L3S Research Center)

A General Optimization Framework for Smoothing Language Models on Graph Structures
Q. Mei, D. Zhang and C. Zhai  (University of Illinois at Urbana-Champaign)

Separate and Inequal: Preserving Heterogeneity in Topical Authority Flows
L. Nie and B. Davison  (Lehigh University)

Algorithmic Mediation for Collaborative Exploratory Search
J. Pickens, G. Golovchinsky, C. Shah, P. Qvarfordt and M. Back  ( FX Palo Alto Lab, Inc./ University of North Carolina)

Classifiers Without Borders: Incorporating Fielded Text From Neighboring Web Pages
X. Qi and B. Davison  (Lehigh University)

TF-IDF Uncovered: A Study of Theories and Probabilities
T. Roelleke and J. Wang  (Queen Mary, University of London)

Towards Breaking the Quality Curse. A Web-Querying Approach to Web People Search.
D.V.Kalashnikov, R.Nuray-Turan and S.Mehrotra (University of California, Irvine)

Efficient Top-k Querying over Social-Tagging Networks
R. Schenkel, T. Crecelius, M. Kacimi, S. Michel, T. Neumann, J. Xavier Parreira and G. Weikum  (EPFL/Max Planck Institute for Computer Science/Max-Planck-Institut Informatik)

Local Text Reuse Detection
J. Seo and B. Croft  (University of Massachusetts, Amherst)

Ambiguous Queries: Test Collections Need More Sense
M. Sanderson  (University of Sheffield)

Real-time Automatic Tag Recommendation
Y. Song, Z. Zhuang, H. Li, Q. Zhao, J. Li, W.c. Lee and C.L. Giles  (The Pennsylvania State University/AOL Research Lab)

ResIn: A Combination of Results Caching and Index Pruning for High-performance Web Search Engines
G. Skobeltsyn, F. Junqueira, V. Plachouras and R. Baeza-Yates (EPFL/Yahoo! Research, Barcelona)

User Adaptation: Good Results from Poor Systems
C. Smith and P. Kantor  (Rutgers University)

A Study of Learning a Merge Model for Multilingual Information Retrieval
M.F. Tsai, Y. Wang and H.H. Chen  (National Taiwan University)

SpotSigs: Robust and Efficient Near Duplicate Detection in Large Web Collections
M. Theobald, J. Siddharth and A. Paepcke  (Stanford University)

To Personalize or Not to Personalize: Modeling Queries with Variation in User Intent
J. Teevan, S.T. Dumais and D.J. Liebling  (Microsoft Research)

Learning to Rank at Query-Time using Association Rules
A. Veloso, H. Almeida, M. Gonçalves and W. Meira Jr.  (UFMG)

A Study of Methods for Negative Relevance Feedback
X. Wang, H. Fang, and C. Zhai  (University of Illinois at Urbana-Champaign/The Ohio State University)

An Unsupervised Framework for Extracting and Normalizing Product Attributes from Multiple Web Sites
T.L. Wong, W. Lam and T.S. Wong  (The Chinese University of Hong Kong)

Automatically Identifying Localizable Queries
M. Welch and J.J. Cho  (UCLA)

Bilingual Topic Aspect Classification with A Few Training Examples
Y. Wu and D. Oard  (University of Maryland)

Discriminative Probabilistic Models for Passage Based Retrieval
M. Wang and L. Si  (Purdue University/Stanford University)

Enhancing Web Search by Promoting Multiple Search Engine Use
R. White, M. Richardson, M. Bilenko and A. Heath  (Microsoft Research)

Exploring Traversal Strategy for Web Forum Crawling
Y. Wang, J. M. Yang, W. Lai, R. Cai, L. Zhang and W. Y. Ma   (Chinese Academy of Science/Microsft Research Asia)

Learning to Reduce the Semantic Gap in Web Image Retrieval and Annotation
C. Wang, L. Zhang and H.J. Zhang  (Microsoft Research Asia/University of Science and Technology of China)

Multi-Document Summarization Using Cluster-Based Link Analysis
X. Wan and J. Yang (Peking University)

Multi-Document Summarization via Sentence-Level Semantic Analysis and Symmetric Matrix Factorization
D. Wang, T. Li, S. Zhu and C. Ding  (Florida International University/NEC Labs. America, Inc/University of Texas at Arlington)

Query-Sensitive Mutual Reinforcement Chain and Its Application in Query-Oriented Multi-Document  Summarization
F. Wei, W. Li, Q. Lu and Y. He  (The Hong Kong Polytechnic University)

Score Standardization for Inter-Collection Comparison of Retrieval Systems
W. Webber, A. Moffat and J. Zobel  (University of Melbourne)

A Bayesian Logistic Regression Model for Active Relevance Feedback
Z. Xu and R. Akella  (University of California, Santa Cruz)

A New Probabilistic Retrieval Model Based on the DirichletCompound Multinomial Distribution
Z. Xu and R. Akella  (University of California, Santa Cruz)

Deep Classification in Large-scale Text Hierarchies
G.R. Xue, D. Xing, Q. Yang and Y. Yu  (Hong Kong Science & Technology University/Shanghai Jiao-Tong University)

Exploring Folksonomy for Personalized Search
S. Xu, S. Bao, B. Fei, Z. Su and Y. Yu  (IBM China Research Lab/Shanghai Jiao Tong University)

Retrieval Models for Question and Answer Archives
X. Xue, J. Jeon and B. Croft  (University of Massachusetts Amherst/Google, Inc.)

Topic-bridged PLSA for Cross-Domain Text Classification
G.R. Xue, W. Dai, Q. Yang and Y. Yu  (Hong Kong Science & Technology University/Shanghai Jiao-Tong University)

A New Rank Correlation Coefficient for Information Retrieval
E. Yilmaz, J. Aslam and S. Robertson  (Microsoft Research/Northeastern University)

A Simple and Efficient Sampling Method for Estimating AP and NDCG
E. Yilmaz, E. Kanoulas and J. Aslam  (Northeastern University)

Non-greedy Active Learning for Text Categorization using Convex Transductive Experimental Design
K. Yu, S. Zhu, W. Xu and Y. Gong  (NEC Labs America)

A Comparative Evaluation of Different Link Types on Enhancing Document Clustering
X. Zhang, X. Hu and X. Zhou  (Drexel University)

Exploiting Correlated Keywords to Improve Approximate Information Filtering
C. Zimmer, C. Tryfonopoulos and G. Weikum  (Max-Planck-Institute for Informatics/Max-Planck Institute for Computer Science)

Learning to Rank with Ties
K. Zhou, G.R. Xue, H. Zha and Y. Yu  (Georgia Tech/Shanghai Jiao-Tong University)