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Discriminative probabilistic models for expert search in heterogeneous information sources

Yi Fang, Luo Si, Aditya P. Mathur
2010 Information retrieval (Boston)  
In many realistic settings of expert finding, the evidence for expertise often comes from heterogeneous knowledge sources.  ...  Beyond just learning a fixed combination strategy for all the queries and experts, we propose a series of discriminative probabilistic models which have increasing capability to associate the combination  ...  Section 3 proposes different discriminative probabilistic models for expert search in heterogeneous information sources. Section 4 presents the experimental results and the corresponding discussions.  ... 
doi:10.1007/s10791-010-9139-3 fatcat:vpadslgd6vcalalojm5boiaw4e

Identifying similar people in professional social networks with discriminative probabilistic models

Suleyman Cetintas, Monica Rogati, Luo Si, Yi Fang
2011 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11  
Information about users can be obtained from heterogeneous information sources, and different sources provide different insights on user similarity.  ...  This paper proposes a discriminative probabilistic model that identifies latent content and graph classes for people with similar profile content and social graph similarity patterns, and learns a specialized  ...  information from these sources in a principled way (e.g., [4] ).  ... 
doi:10.1145/2009916.2010123 dblp:conf/sigir/CetintasRSF11 fatcat:xtk7zzcmuzdbvb2hyvdnactxli

Entity information management in complex networks

Yi Fang
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
In the recent years, entity retrieval especially expert search has attracted much attention in the IR community while many other EIM problems have been rarely investigated.  ...  It is motivated by the increasingly sophisticated user information needs that go beyond document search.  ...  homepage dependence graph/network; 2) Mixture models are proposed in [6] to learn flexible combination strategies to rank experts in heterogeneous information sources; 3) The dependence of table elements  ... 
doi:10.1145/1835449.1835690 dblp:conf/sigir/Fang10 fatcat:v4zgq7fofjbk7jdq2y6j42xpse

Discriminative models of integrating document evidence and document-candidate associations for expert search

Yi Fang, Luo Si, Aditya P. Mathur
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
In this paper, we propose a principled relevance-based discriminative learning framework for expert search and derive specific discriminative models from the framework.  ...  On the other hand, discriminative models have received little attention in expert search research, although they have been shown to outperform generative models in many other information retrieval and  ...  We thank the anonymous reviewers for many valuable comments.  ... 
doi:10.1145/1835449.1835563 dblp:conf/sigir/FangSM10 fatcat:aynchayycrcxtmyhbe7ym3nvse

Expert Finding Systems: A Systematic Review

Omayma Husain, Naomie Salim, Rose Alinda Alias, Samah Abdelsalam, Alzubair Hassan
2019 Applied Sciences  
This review indicated that ≈65% of expert finding systems are used in the academic domain. This review forms a basis for future expert finding systems research.  ...  Moreover, it identifies the contextual factors that have been combined into expert finding systems. Finally, it identifies five gaps in expert finding systems for future research.  ...  We also acknowledge Ministry of Higher Education, Sudan, and University of Khartoum, Faculty of Mathematical Science, Sudan, for sponsoring Omayma Husain in her PhD Program at Universiti Teknologi Malaysia  ... 
doi:10.3390/app9204250 fatcat:scg4q6zzqrewzo5qqf3h7pgpv4

SCSMiner: mining social coding sites for software developer recommendation with relevance propagation

Yao Wan, Liang Chen, Guandong Xu, Zhou Zhao, Jie Tang, Jian Wu
2018 World wide web (Bussum)  
., GitHub) can integrate social networking and distributed version control in a unified platform to facilitate collaborative developments over the world.  ...  In [23] , a discriminative learning framework is proposed for expert finding and two specific probabilistic models i.e., the arithmetic mean discriminative model and the geometric mean discriminative  ...  Preliminaries In this section, we introduce the information we can get from a SCS, and formally define the problem of expertise search and ranking in a heterogeneous network.  ... 
doi:10.1007/s11280-018-0526-9 fatcat:36y5f5z6rbdaplj3iqb4ofs7ou

The QMUL Team with Probabilistic SQL at Enterprise Track

Thomas Roelleke, Elham Ashoori, Hengzhi Wu, Zhen Cai
2005 Text Retrieval Conference  
For the less complex retrieval tasks (discussion search, known-item search), minimal resources lead to acceptable results, whereas for the more complex retrieval tasks (expert search), inclusion and combination  ...  Through the consequent usage of our probabilistic variant of SQL, we could describe retrieval strategies within a few lines of code. 2.  ...  In that project, several highly heterogeneous data sources needed to be explored for creating expert profiles, and the customisable ranking of experts in a number of different contexts was required.  ... 
dblp:conf/trec/RoellekeAWC05 fatcat:bbnfx47p7ff2hfz3dhj34b5ayq

Expertise Retrieval

Krisztian Balog
2012 Foundations and Trends in Information Retrieval  
Section 5 continues with an overview of approaches and includes probabilistic models (generative and discriminative), voting models, graph-based models, as well as methods that do not fall under any of  ...  The heterogeneous nature of expertise evidence is discussed throughout the survey, for instance in Sections 2.3, as part of our discussions of models for expertise retrieval in Section 5, in advanced components  ... 
doi:10.1561/1500000024 fatcat:yl5fff5mbrbozfr3qnrv3osyte

Guest Editorial: Introduction to the Special Issue on Advances in Semantic Computing

Phillip C.-Y. Sheu, Arif Ghafoor
2015 IEEE Transactions on Emerging Topics in Computing  
In ''Discover the expert: Context-adaptive expert selection for medical diagnosis'', Cem Tekin, Onur Atan, and Mihaela van der Schaar propose an expert selection system that learns online the best expert  ...  If the most relevant context information can be identified for a patient, it is believed that the best clinic and expert for the diagnosis can be recommended for that patient.  ... 
doi:10.1109/tetc.2015.2432332 fatcat:luubzsq7jzbljnnitdwntdnhnm

A Review of Characterization Approaches for Smallholder Farmers: Towards Predictive Farm Typologies

Devotha G. Nyambo, Edith T. Luhanga, Zaipuna Q. Yonah
2019 The Scientific World Journal  
than two unsupervised learning algorithms by using training models, (b) assess the training models' robustness in predicting farm types for a testing dataset, and (c) assess the predictive power of the  ...  Characterization of smallholder farmers has been conducted in various researches by using machine learning algorithms, participatory and expert-based methods.  ...  , available sources of information, and the importance of a particular technology to the farmers.  ... 
doi:10.1155/2019/6121467 fatcat:l4v6g5hlbzgt3ae5owhjkp7k4u

Modeling Multi-View Dependence in Bayesian Networks for Alzheimer's Disease Detection

Parvathy Sudhir Pillai, Tze-Yun Leong, Alzheimer's Disease Neuroimaging Initiative
2019 Studies in Health Technology and Informatics  
We learn the dependence structure from data with guidance from domain knowledge in Bayesian Networks, visualizing and quantifying the conditional probabilistic dependence among the variables.  ...  We propose a multi-view dependence modeling framework that integrates multiple data sources to distinguish patients at different stages of the disease.  ...  Data used in the preparation of this article was obtained from the ADNI database [5] .  ... 
doi:10.3233/shti190243 pmid:31437945 fatcat:nqwv3hefjbevjpy5trg4tz55su

Semantic-based Expert Search in Textbook Research Archives

Marco Pavan, Ernesto William De Luca
2015 International Conference on Theory and Practice of Digital Libraries  
An heterogeneous environment, with possible lack of information, and not well structured data, puts forward new challenges, to address the problem of adapting user profiling and consequently expert search  ...  We conjecture that the CKG allows to model users emphasizing new semantic aspects of relationships among profile elements, and helps to improve the similarity computation and the expert search.  ...  [4] propose a discriminative probabilistic model that identifies latent content and graph classes for people with similar profile. Moreira et al.  ... 
dblp:conf/ercimdl/PavanL15 fatcat:62ry5ujd4fdbxpbcszc6kelbp4

Probabilistic latent query analysis for combining multiple retrieval sources

Rong Yan, Alexander G. Hauptmann
2006 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '06  
To merge retrieval sources adaptively according to query topics, we propose a series of new approaches called probabilistic latent query analysis (pLQA), which can associate non-identical combination weights  ...  Combining the output from multiple retrieval sources over the same document collection is of great importance to a number of retrieval tasks such as multimedia retrieval, web retrieval and meta-search.  ...  Acknowledgement This work was supported in part by the Advanced Research and Development Activity (ARDA) under contract number H98230-04-C-0406 and NBCHC040037, and by the National Science Foundation under  ... 
doi:10.1145/1148170.1148228 dblp:conf/sigir/YanH06 fatcat:r2cri2qq4bg37jl4e3ecq2lsn4

Discovery of biological networks from diverse functional genomic data

Chad L Myers, Drew Robson, Adam Wible, Matthew A Hibbs, Camelia Chiriac, Chandra L Theesfeld, Kara Dolinski, Olga G Troyanskaya
2005 Genome Biology  
We have developed a general probabilistic system for query-based discovery of pathway-specific networks through integration of diverse genome-wide data.  ...  This framework was validated by accurately recovering known networks for 31 biological processes in Saccharomyces cerevisiae and experimentally verifying predictions for the process of chromosomal segregation  ...  Materials and methods Our method relies on four critical components: Bayesian integration of heterogeneous data; an expert-driven search paradigm; a probabilistic graph search algorithm; and an easily  ... 
doi:10.1186/gb-2005-6-13-r114 pmid:16420673 pmcid:PMC1414113 fatcat:zbwq3u3eufebrdbwqlikgteljq

Data challenges of time domain astronomy

Matthew J. Graham, S. G. Djorgovski, Ashish Mahabal, Ciro Donalek, Andrew Drake, Giuseppe Longo
2012 Distributed and parallel databases  
This brings both new scientific opportunities and fresh challenges, in terms of data rates from robotic telescopes and exponential complexity in linked data, but also for data mining algorithms used in  ...  We review our experiences with the Palomar-Quest and Catalina Real-Time Transient Sky Surveys; in particular, addressing the issue of the heterogeneity of data associated with transient astronomical events  ...  We are thankful to numerous colleagues in the VO and Astroinformatics community, and to the members of the DPOSS, PQ, and CRTS survey teams, for many useful discussions and interactions through the years  ... 
doi:10.1007/s10619-012-7101-7 fatcat:iwtdmexuqzefjmzucdtqtd22ae
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