This work together with Arjen P. de Vries and Kevyn Collins-Thompson has been accepted for full oral presentation at the 36th Annual International ACM Conference on Research and Development in Information Retrieval (SIGIR) in Dublin, Ireland.

• Claudio Carpineto et al. – Semantic Search Log k-Anonymization with Generalized k-Cores of Query Concept Graph. (shared best paper) For k-anonymization of search engine log files, unique or infrequent queries can be removed in order to prevent individual users from being identifiable. Massive pruning can, however, significantly reduce the coverage of log files. The authors propose a clustering method to anonymize log files based on query similarity rather than identity.
• Yashar Moshfeghi et al. – Understanding Relevance: An fMRI Study. (shared best paper) Are there neural differences in the processing of relevant and non-relevant documents? How does the human brain react to relevance? The authors show a first investigation into this domain.
• Aleksandr Chuklin et al. – Using Intent Information to Model User Behavior in Diversified Search. (best student paper) The authors propose an intent-aware click model to estimate relevance based on the user’s underlying search intent.
• Marc Bron et al. – Example Based Entity Search in the Web of Data. Using positive examples for entity search, the authors show performance gains when enriching entity queries with knowledge gained from the context of provided examples.
• Van Dang et al. – Two-Stage Learning
  to Rank for Information Retrieval. The authors introduce a multi-stage bootstrapped learning to rank process.
• Dongyi Guan et al. – Increasing Stability of Result Organization for Session Search. For faceted search, the authors employ external resources such as Wikipedia to improve the performance of the underlying result clustering.
• Xiaofei Zhu et al. – Recommending High Utility Query via Session-Flow Graph. Based on random walks in the clickthrough graph, the authors motivate a query recommendations scheme that focuses on high-utility queries. Such queries have been estimated to return more useful results for the user.
• Maksim Zhukovskii et al. – URL Redirection Accounting for Improving Link-Based Ranking Methods. The authors show how redirections can significantly obscure web graphs used to compute PageRank and other structural quality indicators.
• Nima Asadi et al. – Training Efficient Tree-Based Models for Document Ranking. The authors investigate the balanced creation of CART trees for LambdaMART learning to rank schemes. By biasing algorithms towards balanced, shallow tree ensembles, they show significant efficiency gains at only minuscule losses in ranking performance.

This work together with Wen Li and Arjen P. de Vries has been accepted for full oral presentation at the 35th European Conference on Information Retrieval (ECIR) in Moscow, Russia.

This work together with Kevyn Collins-Thompson, Paul Bennett and Susan Dumais has been accepted for poster presentation at the 35th European Conference on Information Retrieval (ECIR) in Moscow, Russia.

This work together with Kevyn Collins-Thompson, Paul Bennett and Susan Dumais has been accepted for full oral presentation at the ACM International Conference on Web Search and Data Mining (WSDM) in Rome, Italy.

• Ben Carterette et al. – Incorporating in User Behavior into Systems Based Evaluation. The authors propose a log-file-based user modeling scheme for system evaluation, representing variability in user behavior in the form of distributions rather than point estimates.
• Shahzad Rajput et al. – Constructing Test Collections by Inferring Document Relevance via Extracted Relevant Information. The authors demonstrate how passage-level relevance judgements can be propagated across documents in order to make the judging process more efficient.
• Jin Young Kim et al. – Understanding Book Search Behavior on the Web. Based on 6 months of log file data of the open library, the authors show a detailed overview how and with which tools users search for books online. The resulting dataset is openly available to the research community.
• Mark Sanderson et al. – Differences in Effectiveness across Sub-Collections. Different test collections have previously been reported to affect retrieval system performance scores. In this work, the authors quantify this effect by creating subsets of well-known collections.
• Mark Smucker et al. – Stochastic Simulation of Time-Biased Gain. The authors expand on the previously (SIGIR’12 best paper) introduced performance metric time-biased gain and propose a stochastic simulation for the score’s numerical approximation.
• Theodoros Lappas et al. – Customizing Search Results for Non-Native Speakers. The authors employ complexity of foreign language text as well as its similarity to the reader’s native tongue as a quality criterion in document ranking.

• Van Dang and Bruce Croft – Diversity by Proportionality: An Election-based Approach to Search Result Diversification The authors propose a voting algorithm that takes into account the underlying aspect proportions of diverse queries.
• Ryen White and Eric Horvitz – Studies of the Onset and Persistence of Medical Concerns in Search Logs. The authors investigate medical web search sessions as expressed in search engine log files. According to their analysis, 80% of their users showcase medical search sessions over a period of several months. Most notably, sympton-driven searches were found to precede concrete conditions by significant time.
• Patrick Pantel et al. – Social Annotations on the Search Results Page: Utility and Prediction Modeling. This work uses social network annotations such as likes, dislikes and expressions of expertise to augment search engine result pages. The evaluation is based on a large-scale simulated social network.
• Eugene Agichtein et al. – Search, Interrupted: Understanding and Predicting Search Task Continuation . Some search tasks continue across session boundaries and resurface across extended stretches of time. The authors identify properties of continuing search task in order to predict whether a given task will end with the current session or resurface at a later point in time.
• Brent Hecht et al. – Explanatory Semantic Relatedness and Explicit Spatialization for Exploratory Search. The authors presented Atlasify, a system for exploring the relatedness of topical and spatial domain of search queries.
• Yu-Heng Lei et al. – Where Is Who: Large-Scale Photo Retrieval by Facial Attributes and Canvas Layout . A sketch-based image retrieval system powered by number and position of people in the images. Face recognition further helps to refine queries by specifying who to search for.
• Mehdi Hosseini et al. – An Uncertainty-aware Query Selection Model for Evaluation of IR Systems. The authors propose a query selection framework to identify the most effective subset of queries for the formation of evaluation corpora.

This paper has been accepted for publication at CIKM’12, Maui, USA.

BooksOnline’12 will encourage strong exploitation of the incentives and benefits of these major forms of massive on-line collaborations for digital libraries.

Workshop Format

The one day workshop will include selected oral and poster sessions to present and discuss ongoing research efforts, and a break-out session to brainstorm around new ideas, research directions, proposals and implementation strategies, finishing with presentations to summarize the results of the break-out sessions
Similarly to previous years, we plan to host keynote speakers, who are prominent in the area. Previous keynote speakers included Adam Farquhar (The British Library), Ville Miettinnen (Microtask), James Crawford (Google Books), John Ockerbloom (University of Pennsylvania), and Brewster Kahle (Internet Archive).

Find out more at: http://www.hci.usi.ch/BooksOnline12/