BibSLEIGH — Craig

Travelled to:

1 × Australia
1 × Canada
1 × Chile
1 × France
1 × Italy
1 × Portugal
1 × Russia
1 × Singapore
1 × Spain
2 × Ireland
2 × The Netherlands
3 × China
3 × United Kingdom
7 × USA

Collaborated with:

I.Ounis R.L.T.Santos R.McCreadie N.Limsopatham B.He N.Tonellotto J.Peng M.Albakour E.Kharitonov P.Serdyukov I.Soboroff M.Catena B.T.Dinçer D.Hannah R.W.White D.McDougall R.Deveaud A.Freire F.Cacheda V.Plachouras G.D.Santo G.McDonald T.Gollins J.He A.Fang P.Habel A.Vorobev J.Manotumruksa C.L.A.Clarke V.Bicer J.Giles F.Jabr J.Lin D.McCullough G.Amati D.Johnson D.Broccolo S.Orlando R.Perego F.Silvestri

Talks about:

search (27) rank (11) use (11) queri (9) retriev (8) expert (8) learn (8) sensit (7) opinion (6) select (6)

Person: Craig Macdonald

DBLP: Macdonald:Craig

Facilitated 2 volumes:

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

Wrote 66 papers:

SIGIR-2015-AlbakourMO #data type #identification #metadata #topic #using: Using Sensor Metadata Streams to Identify Topics of Local Events in the City (MDA, CM, IO), pp. 711–714.
SIGIR-2015-CatenaMT #cpu #power management #web: Load-sensitive CPU Power Management for Web Search Engines (MC, CM, NT), pp. 751–754.
SIGIR-2015-FangOHML #classification #topic #twitter: Topic-centric Classification of Twitter User’s Political Orientation (AF, IO, PH, CM, NL), pp. 791–794.
SIGIR-2015-KharitonovMSO #online #scheduling: Optimised Scheduling of Online Experiments (EK, CM, PS, IO), pp. 453–462.
SIGIR-2015-KharitonovVMSO #online #testing: Sequential Testing for Early Stopping of Online Experiments (EK, AV, CM, PS, IO), pp. 473–482.
SIGIR-2015-SantoMMO #query: Comparing Approaches for Query Autocompletion (GDS, RM, CM, IO), pp. 775–778.
CIKM-2014-DeveaudAMMO #named #personalisation #recommendation: SmartVenues: Recommending Popular and Personalised Venues in a City (RD, MDA, JM, CM, IO), pp. 2078–2080.
CIKM-2014-DeveaudAMO #learning #on the #rank: On the Importance of Venue-Dependent Features for Learning to Rank Contextual Suggestions (RD, MDA, CM, IO), pp. 1827–1830.
CIKM-2014-LimsopathamMO #modelling #multi #ranking #towards: Modelling Relevance towards Multiple Inclusion Criteria when Ranking Patients (NL, CM, IO), pp. 1639–1648.
CIKM-2014-McCreadieMO #adaptation #incremental #summary: Incremental Update Summarization: Adaptive Sentence Selection based on Prevalence and Novelty (RM, CM, IO), pp. 301–310.
ECIR-2014-AlbakourMOCB #information management: Information Access in Smart Cities (i-ASC) (MDA, CM, IO, CLAC, VB), pp. 810–814.
ECIR-2014-CatenaMO #on the #performance: On Inverted Index Compression for Search Engine Efficiency (MC, CM, IO), pp. 359–371.
ECIR-2014-DincerOM #evaluation #retrieval: Tackling Biased Baselines in the Risk-Sensitive Evaluation of Retrieval Systems (BTD, IO, CM), pp. 26–38.
ECIR-2014-McDonaldMOG #classification #overview #perspective #towards: Towards a Classifier for Digital Sensitivity Review (GM, CM, IO, TG), pp. 500–506.
SIGIR-2014-DincerMO #evaluation #retrieval #testing: Hypothesis testing for the risk-sensitive evaluation of retrieval systems (BTD, CM, IO), pp. 23–32.
CIKM-2013-AlbakourMO #effectiveness #microblog #on the #realtime: On sparsity and drift for effective real-time filtering in microblogs (MDA, CM, IO), pp. 419–428.
CIKM-2013-BroccoloMOOPST #distributed: Load-sensitive selective pruning for distributed search (DB, CM, SO, IO, RP, FS, NT), pp. 379–388.
CIKM-2013-KharitonovMSO #using: Using historical click data to increase interleaving sensitivity (EK, CM, PS, IO), pp. 679–688.
ECIR-2013-FreireMTOC #hybrid #query #scheduling: Hybrid Query Scheduling for a Replicated Search Engine (AF, CM, NT, IO, FC), pp. 435–446.
ECIR-2013-LimsopathamMO: Aggregating Evidence from Hospital Departments to Improve Medical Records Search (NL, CM, IO), pp. 279–291.
ECIR-2013-LimsopathamMO13a #documentation #query #representation: A Task-Specific Query and Document Representation for Medical Records Search (NL, CM, IO), pp. 747–751.
SIGIR-2013-KharitonovMSO #evaluation #metric #modelling #query: User model-based metrics for offline query suggestion evaluation (EK, CM, PS, IO), pp. 633–642.
SIGIR-2013-LimsopathamMO #learning: Learning to combine representations for medical records search (NL, CM, IO), pp. 833–836.
SIGIR-2013-McCreadieMO #what: News vertical search: when and what to display to users (RM, CM, IO), pp. 253–262.
CIKM-2012-MacdonaldSO #learning #on the #query #rank: On the usefulness of query features for learning to rank (CM, RLTS, IO), pp. 2559–2562.
CIKM-2012-McCreadieMOGJ #crowdsourcing #using #web: An examination of content farms in web search using crowdsourcing (RM, CM, IO, JG, FJ), pp. 2551–2554.
SIGIR-2012-FreireMTOC #query #scheduling: Scheduling queries across replicas (AF, CM, NT, IO, FC), pp. 1139–1140.
SIGIR-2012-LimsopathamMMO #dependence: Exploiting term dependence while handling negation in medical search (NL, CM, RM, IO), pp. 1065–1066.
SIGIR-2012-MacdonaldTO #learning #online #predict #query #scheduling: Learning to predict response times for online query scheduling (CM, NT, IO), pp. 621–630.
SIGIR-2012-MacdonaldTO12a #effectiveness #learning #rank #safety: Effect of dynamic pruning safety on learning to rank effectiveness (CM, NT, IO), pp. 1051–1052.
SIGIR-2012-McCreadieMO #automation #crowdsourcing #named: CrowdTerrier: automatic crowdsourced relevance assessments with terrier (RM, CM, IO), p. 1005.
SIGIR-2012-McCreadieSLMOM #corpus #on the #reuse #twitter: On building a reusable Twitter corpus (RM, IS, JL, CM, IO, DM), pp. 1113–1114.
CIKM-2011-SantosMO #effectiveness: Effectiveness beyond the first crawl tier (RLTS, CM, IO), pp. 1937–1940.
ECIR-2011-MacdonaldO #learning #modelling #ranking: Learning Models for Ranking Aggregates (CM, IO), pp. 517–529.
SIGIR-2011-LimsopathamSMO #using: Disambiguating biomedical acronyms using EMIM (NL, RLTS, CM, IO), pp. 1213–1214.
SIGIR-2011-SantosMO: Intent-aware search result diversification (RLTS, CM, IO), pp. 595–604.
SIGIR-2011-SantosMO11a #metric #on the #ranking: On the suitability of diversity metrics for learning-to-rank for diversity (RLTS, CM, IO), pp. 1185–1186.
SIGIR-2011-SantosMO11b #how #question #web: How diverse are web search results? (RLTS, CM, IO), pp. 1187–1188.
SIGIR-2011-TonellottoMO #order #retrieval: Effect of different docid orderings on dynamic pruning retrieval strategies (NT, CM, IO), pp. 1179–1180.
CIKM-2010-SantosMO #web: Selectively diversifying web search results (RLTS, CM, IO), pp. 1179–1188.
ECIR-2010-PengMO #learning #ranking: Learning to Select a Ranking Function (JP, CM, IO), pp. 114–126.
ECIR-2010-SantosPMO: Explicit Search Result Diversification through Sub-queries (RLTS, JP, CM, IO), pp. 87–99.
CIKM-2009-MacdonaldO #documentation #ranking: The influence of the document ranking in expert search (CM, IO), pp. 1983–1986.
CIKM-2009-PengMHO #case study #enterprise: A study of selective collection enrichment for enterprise search (JP, CM, BH, IO), pp. 1999–2002.
ECIR-2009-SantosHMO #proximity #retrieval: Integrating Proximity to Subjective Sentences for Blog Opinion Retrieval (RLTS, BH, CM, IO), pp. 325–336.
SIGIR-2009-MacdonaldO #documentation #on the #ranking: On perfect document rankings for expert search (CM, IO), pp. 740–741.
SIGIR-2009-MacdonaldOS #question: Is spam an issue for opinionated blog post search? (CM, IO, IS), pp. 710–711.
SIGIR-2009-MacdonaldW: Usefulness of click-through data in expert search (CM, RWW), pp. 816–817.
SIGIR-2009-McCreadieMO #on the #pipes and filters: On single-pass indexing with MapReduce (RM, CM, IO), pp. 742–743.
SIGIR-2009-McDougallM #using: Expertise search in academia using facets (DM, CM), p. 834.
CIKM-2008-HeMHO #approach #effectiveness #retrieval #statistics: An effective statistical approach to blog post opinion retrieval (BH, CM, JH, IO), pp. 1063–1072.
CIKM-2008-MacdonaldO #ranking: Key blog distillation: ranking aggregates (CM, IO), pp. 1043–1052.
ECIR-2008-HannahMO #analysis #graph: Analysis of Link Graph Compression Techniques (DH, CM, IO), pp. 596–601.
ECIR-2008-MacdonaldHO #quality: High Quality Expertise Evidence for Expert Search (CM, DH, IO), pp. 283–295.
ECIR-2008-MacdonaldO #documentation #evaluation: Expert Search Evaluation by Supporting Documents (CM, IO), pp. 555–563.
SIGIR-2008-HeMO #metric #retrieval #using: Retrieval sensitivity under training using different measures (BH, CM, IO), pp. 67–74.
SIGIR-2008-HeMO08a #ranking #using: Ranking opinionated blog posts using OpinionFinder (BH, CM, IO), pp. 727–728.
SIGIR-2008-MacdonaldHOS: Limits of opinion-finding baseline systems (CM, BH, IO, IS), pp. 747–748.
SIGIR-2008-PengMO #automation #documentation #feature model #retrieval #web: Automatic document prior feature selection for web retrieval (JP, CM, IO), pp. 761–762.
CIKM-2007-MacdonaldO #query: Expertise drift and query expansion in expert search (CM, IO), pp. 341–350.
ECIR-2007-MacdonaldO #feedback #using: Using Relevance Feedback in Expert Search (CM, IO), pp. 431–443.
SIGIR-2007-PengMHPO #dependence #framework: Incorporating term dependency in the dfr framework (JP, CM, BH, VP, IO), pp. 843–844.
CIKM-2006-MacdonaldO #adaptation #data fusion: Voting for candidates: adapting data fusion techniques for an expert search task (CM, IO), pp. 387–396.
SIGIR-2006-MacdonaldO #email: Combining fields in known-item email search (CM, IO), pp. 675–676.
SIGIR-2006-MacdonaldO06a #framework #platform #using: Searching for expertise using the terrier platform (CM, IO), p. 732.
ECIR-2005-OunisAPHMJ #framework #information retrieval #platform: Terrier Information Retrieval Platform (IO, GA, VP, BH, CM, DJ), pp. 517–519.