BibSLEIGH — Djoerd

Travelled to:

1 × Chile
1 × Finland
1 × France
1 × Germany
1 × Russia
1 × Singapore
1 × Spain
1 × Switzerland
1 × The Netherlands
2 × Canada
2 × China
2 × Ireland
4 × USA
4 × United Kingdom

Collaborated with:

P.Serdyukov F.d.Jong H.Rode D.Trieschnigg ∅ C.Hauff S.D.Torres L.Azzopardi T.Demeester J.Kamps K.Tjin-Kam-Jet P.M.G.Apers H.Zaragoza D.Nguyen I.Weber R.Aly W.Kraaij R.Kaptein H.E.Blok M.Moens T.Westerveld V.Mihajlovic S.E.Robertson M.E.Tipping T.W.C.Huibers F.Kruisinga F.v.d.Sluis M.Neshati E.Asgari H.Beigy A.Kulkarni A.S.Tigelaar J.Callan A.R.Doherty A.F.Smeaton R.Li M.M.Fokkinga A.P.d.Vries K.Zhou C.Develder B.v.Dijk G.Ramírez S.Choenni H.M.Blanken J.Kiseleva M.J.I.Müller L.Bernardi C.Davis I.Kovacek M.S.Einarsen A.Tuzhilin D.Dowie C.Eickhoff R.Glassey K.Gyllstrom K.A.Marshall S.Moens T.Polajnar

Talks about:

inform (13) retriev (12) model (11) search (10) queri (9) languag (7) children (5) expert (5) predict (4) find (4)

Person: Djoerd Hiemstra

DBLP: Hiemstra:Djoerd

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

1999

1998

2013

Wrote 42 papers:

SIGIR-2015-KiselevaMBDKEKT #optimisation: Where to Go on Your Next Trip?: Optimizing Travel Destinations Based on User Preferences (JK, MJIM, LB, CD, IK, MSE, JK, AT, DH), pp. 1097–1100.
CIKM-2014-ZhouDNHT: Aligning Vertical Collection Relevance with User Intent (KZ, TD, DN, DH, DT), pp. 1915–1918.
ECIR-2013-DemeesterNTDH #predict #web: Snippet-Based Relevance Predictions for Federated Web Search (TD, DN, DT, CD, DH), pp. 697–700.
ECIR-2013-NeshatiAHB #classification #network #social: A Joint Classification Method to Integrate Scientific and Social Networks (MN, EA, DH, HB), pp. 122–133.
ECIR-2013-WeberHS: From Republicans to Teenagers — Group Membership and Search (GRUMPS) (IW, DH, PS), pp. 886–889.
SIGIR-2013-AlyHD #named #using: Taily: shard selection using the tail of score distributions (RA, DH, TD), pp. 673–682.
SIGIR-2013-TrieschniggTH #named: SearchResultFinder: federated search made easy (DT, KTKJ, DH), pp. 1113–1114.
CIKM-2012-KulkarniTHC #estimation #ranking #topic: Shard ranking and cutoff estimation for topically partitioned collections (AK, AST, DH, JC), pp. 555–564.
CIKM-2012-NguyenDTH #power of: Federated search in the wild: the combined power of over a hundred search engines (DN, TD, DT, DH), pp. 1874–1878.
CIKM-2012-TorresHWS #query #recommendation: Query recommendation for children (SDT, DH, IW, PS), pp. 2010–2014.
ECIR-2012-AzzopardiDTEGGHJKMMPSV #named: EmSe: Supporting Children’s Information Needs within a Hospital Environment (LA, DD, SDT, CE, RG, KG, DH, FdJ, FK, KAM, SM, TP, FvdS, APdV), pp. 578–580.
ECIR-2011-SluisTHDK #health #visual notation: Visual Exploration of Health Information for Children (FvdS, SDT, DH, BvD, FK), pp. 788–792.
ECIR-2011-Tjin-Kam-JetTH #web: Free-Text Search versus Complex Web Forms (KTKJ, DT, DH), pp. 670–674.
CIKM-2010-TrieschniggHJK #framework #information retrieval: A cross-lingual framework for monolingual biomedical information retrieval (DT, DH, FdJ, WK), pp. 169–178.
ECIR-2010-AlyDHS #concept #modelling #retrieval #using: Beyond Shot Retrieval: Searching for Broadcast News Items Using Language Models of Concepts (RA, ARD, DH, AFS), pp. 241–252.
ECIR-2010-HauffAHJ #effectiveness #evaluation #performance #predict #query: Query Performance Prediction: Evaluation Contrasted with Effectiveness (CH, LA, DH, FdJ), pp. 204–216.
ECIR-2010-HauffHAJ #automation #evaluation: A Case for Automatic System Evaluation (CH, DH, LA, FdJ), pp. 153–165.
ECIR-2010-KapteinHK #how #modelling #question: How Different Are Language Models andWord Clouds? (RK, DH, JK), pp. 556–568.
SIGIR-2010-TorresHS #analysis #information retrieval #query: Query log analysis in the context of information retrieval for children (SDT, DH, PS), pp. 847–848.
CIKM-2009-HauffHJA #estimation #ranking #set #topic: Relying on topic subsets for system ranking estimation (CH, DH, FdJ, LA), pp. 1859–1862.
ECIR-2009-HauffAH #evaluation #performance #predict #query: The Combination and Evaluation of Query Performance Prediction Methods (CH, LA, DH), pp. 301–312.
ECIR-2009-MoensH #information management #retrieval: Information Extraction and Linking in a Retrieval Context (MFM, DH), pp. 810–813.
CIKM-2008-HauffHJ #overview #performance #predict #query: A survey of pre-retrieval query performance predictors (CH, DH, FdJ), pp. 1419–1420.
CIKM-2008-SerdyukovRH #modelling #multi: Modeling multi-step relevance propagation for expert finding (PS, HR, DH), pp. 1133–1142.
ECIR-2008-Hiemstra: ECIR 2008 Tutorials (DH), pp. 714–715.
ECIR-2008-SerdyukovH #documentation #modelling: Modeling Documents as Mixtures of Persons for Expert Finding (PS, DH), pp. 309–320.
SIGIR-2008-KapteinLHK #modelling #using #web: Using parsimonious language models on web data (RK, RL, DH, JK), pp. 763–764.
SIGIR-2008-RodeSH #ranking: Combining document- and paragraph-based entity ranking (HR, PS, DH), pp. 851–852.
SIGIR-2008-SerdyukovRH #dependence: Exploiting sequential dependencies for expert finding (PS, HR, DH), pp. 795–796.
SIGIR-2008-SerdyukovRH08a #modelling #random: Modeling expert finding as an absorbing random walk (PS, HR, DH), pp. 797–798.
SIGIR-2007-SerdyukovHFA #documentation #generative #modelling: Generative modeling of persons and documents for expert search (PS, DH, MMF, PMGA), pp. 827–828.
ECIR-2006-RodeH #query #using: Using Query Profiles for Clarification (HR, DH), pp. 205–216.
SIGIR-2006-BlokMRWHV #information retrieval #xml: The TIJAH XML information retrieval system (HEB, VM, GR, TW, DH, APdV), p. 725.
CIKM-2005-MihajlovicBHA #algebra #database: Score region algebra: building a transparent XML-R database (VM, HEB, DH, PMGA), pp. 12–19.
SIGIR-2004-HiemstraRZ #information retrieval #modelling: Parsimonious language models for information retrieval (DH, SER, HZ), pp. 178–185.
SIGIR-2003-ZaragozaHT #ad hoc #information retrieval: Bayesian extension to the language model for ad hoc information retrieval (HZ, DH, MET), pp. 4–9.
SIGIR-2002-Hiemstra #approach #information retrieval #modelling #query: Term-specific smoothing for the language modeling approach to information retrieval: the importance of a query term (DH), pp. 35–41.
SIGIR-2002-KraaijWH: The Importance of Prior Probabilities for Entry Page Search (WK, TW, DH), pp. 27–34.
CIKM-2001-BlokHCJBA #database #design #information retrieval #optimisation #predict #query #trade-off: Predicting the Cost-Quality Trade-Off for Information Retrieval Queries: Facilitating Database Design and Query Optimization (HEB, DH, SC, FdJ, HMB, PMGA), pp. 207–214.
ECDL-1999-HiemstraJ #ambiguity #information retrieval: Disambiguation Strategies for Cross-Language Information Retrieval (DH, FdJ), pp. 274–293.
ECDL-1998-Hiemstra #information retrieval #motivation #probability: A Linguistically Motivated Probabilistic Model of Information Retrieval (DH), pp. 569–584.
JCDL-2013-TorresHH: Vertical selection in the information domain of children (SDT, DH, TWCH), pp. 57–66.