Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
The following results are related to Digital Humanities and Cultural Heritage. Are you interested to view more results? Visit OpenAIRE - Explore.
8 Research products, page 1 of 1

  • Digital Humanities and Cultural Heritage
  • European Commission
  • LIMOSINE
  • Building Rich Links to Enable Television History Research
  • Semantic Search in E-Discovery

Date (most recent)
arrow_drop_down
  • Open Access English
    Authors: 
    Graus, D.; Peetz, M.-H.; Odijk, D.; de Rooij, O.; de Rijke, M.; d'Aquin, M.; Dietze, S.; Drachsler, H.; Guy, M.; Herder, E.;
    Publisher: CEUR-WS
    Country: Netherlands
    Project: NWO | Modeling and Learning fro... (2300171779), NWO | SPuDisc: Searching Public... (2300176811), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702), NWO | Semantic Search in E-Disc... (2300168486)

    In this paper we present yourHistory: a Facebook application that aims to generate a tailor-made, personalized timeline of historic events, by matching a semantically enriched Facebook profile to a pool of candidate historic events extracted from DBPedia. Two aspects are central to our application: (i) semantic linking technologies backed by rich open web knowledge bases for generating semantically enriched user profiles, and (ii) semantic relatedness metrics for ranking historic events to user profiles. This paper describes the development of a Facebook application that aims to be engaging for users, whilst at the same time being a source for data that can be applied to evaluating or improving the application. We describe our Wikipedia-based semantic relatedness metric for event ranking, but also the restrictions and constraints concerning privacy-sensitive and ethical matters, around data storage and user consent. Finally, we reflect on how this type of user data can be applied for evaluating or improving both the semantic linking and event ranking methods in future work.

  • Open Access English
    Authors: 
    Huijnen, Pim; Laan, Fons; de Rijke, Maarten; Pieters, Toine; Nadamoto, A; Jatowt, A; Wierzbicki, A; Leidner, JL; Sub History and Philosophy of Science; Sub Pharmacoepidemiology; +3 more
    Country: Netherlands
    Project: NWO | Modeling and Learning fro... (2300171779), NWO | SPuDisc: Searching Public... (2300176811), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702), NWO | Semantic Search in E-Disc... (2300168486)

    Comparative historical research on the the intensity, diversity and fluidity of public discourses has been severely hampered by the extraordinary task of manually gathering and processing large sets of opinionated data in news media in different countries. At most 50,000 documents have been systematically studied in a single comparative historical project in the subject area of heredity and eugenics. Digital techniques, like the text mining tools WAHSP and BILAND we have developed in two successive demonstrator projects, are able to perform advanced forms of multi-lingual text-mining in much larger data sets of newspapers. We describe the development and use of WAHSP and BILAND to support historical discourse analysis in large digitized news media corpora. Furthermore, we argue how text mining techniques overcome the problem of traditional historical research that only documents explicitly referring to eugenics issues and debates can be incorporated. Our tools are able to provide information on ideas and notions about heredity, genetics and eugenics that circulate in discourses that are not directly related to eugenics (e.g., sport, education and economics).

  • Publication . Article . Preprint . 2013 . Embargo End Date: 01 Jan 2013
    Open Access
    Authors: 
    Zoghi, M.; Whiteson, S.; Munos, R.; de Rijke, M.;
    Publisher: arXiv
    Country: Netherlands
    Project: NWO | SPuDisc: Searching Public... (2300176811), NWO | Semantic Search in E-Disc... (2300168486), EC | LIMOSINE (288024), NWO | Modeling and Learning fro... (2300171779), NWO | Digging archaeology data:... (2300186891), NWO | Building Rich Links to En... (2300153702), EC | COMPLACS (270327)

    This paper proposes a new method for the K-armed dueling bandit problem, a variation on the regular K-armed bandit problem that offers only relative feedback about pairs of arms. Our approach extends the Upper Confidence Bound algorithm to the relative setting by using estimates of the pairwise probabilities to select a promising arm and applying Upper Confidence Bound with the winner as a benchmark. We prove a finite-time regret bound of order O(log t). In addition, our empirical results using real data from an information retrieval application show that it greatly outperforms the state of the art. Comment: 13 pages, 6 figures

  • Publication . Conference object . 2013
    Open Access English
    Authors: 
    Kenter, T.; Graus, D.; Meij, E.; de Rijke, M.;
    Publisher: Microsoft Research
    Country: Netherlands
    Project: NWO | Modeling and Learning fro... (2300171779), NWO | SPuDisc: Searching Public... (2300176811), NWO | Building Rich Links to En... (2300153702), EC | LIMOSINE (288024), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)

    Document filtering over time is applied in tasks such as tracking topics in online news or social media. We consider it a classification task, where topics of interest correspond to classes, and the feature space consists of the words associated to each class. In streaming settings the set of words associated with a concept may change. In this paper we employ a multinomial Naive Bayes classifier and perform periodic feature selection to adapt to evolving topics. We propose two ways of employing Pearson's χ2 test for feature selection and demonstrate their benefit on the TREC KBA 2012 data set. By incorporating a time-dependent function in our equations for χ2 we provide an elegant method for applying different weighting and windowing schemes. Experiments show improvements of our approach over a non-adaptive baseline, in a realistic settings with limited amounts of training data.

  • Publication . Conference object . 2013
    Open Access English
    Authors: 
    Reinanda, R.; Odijk, D.; de Rijke, M.;
    Publisher: Microsoft Research
    Country: Netherlands
    Project: NWO | SPuDisc: Searching Public... (2300176811), NWO | Modeling and Learning fro... (2300171779), NWO | Building Rich Links to En... (2300153702), EC | LIMOSINE (288024), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)

    We address the problem of entity-oriented search in the humanities and social sciences domain. We are particularly interested in retrieving entities related to a query entity and finding associations between these entities over time. Evidence from our target end users suggests that it is more informative to view these associations as dynamic phenomena that evolve over time than as static phenomena. We present work-in-progress on methods to extract these associations and their temporal extent, and discuss a way of presenting them in an exploratory search interface. This interface is intended to help users to discover interesting associations between entities over time

  • Other research product . Other ORP type . 2013
    Open Access
    Authors: 
    Reinanda, R.; Odijk, D.; de Rijke, M.;
    Publisher: TAIA '13
    Country: Netherlands
    Project: NWO | SPuDisc: Searching Public... (2300176811), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486), NWO | Modeling and Learning fro... (2300171779), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702)
  • Publication . Part of book or chapter of book . 2012
    Open Access English
    Authors: 
    de Rijke, M.; Jijkoun, V.; Laan, F.; Weerkamp, W.; Ackermans, P.; Geleijnse, G.; Spyns, P.; Odijk, J.;
    Country: Netherlands
    Project: NWO | Building Rich Links to En... (2300153702), EC | LIMOSINE (288024), NWO | Content-based Literature ... (2300152116), NWO | DutchSemCor: 1 million te... (2300154091), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)

    In order to use a sentiment extraction system for a media analysis problem, a system would have to be able to determine which of the extracted sentiments are relevant, i.e., it would not only have to identify targets of extracted sentiments, but also decide which targets are relevant for the topic at hand.

  • Open Access English
    Authors: 
    de Rijke, Maarten; Jijkoun, Valentin; Laan, Fons; Weerkamp, Wouter; Ackermans, Paul; Geleijnse, Gijs;
    Publisher: Springer Berlin Heidelberg
    Project: NWO | Content-based Literature ... (2300152116), NWO | DutchSemCor: 1 million te... (2300154091), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)
Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
The following results are related to Digital Humanities and Cultural Heritage. Are you interested to view more results? Visit OpenAIRE - Explore.
8 Research products, page 1 of 1
  • Open Access English
    Authors: 
    Graus, D.; Peetz, M.-H.; Odijk, D.; de Rooij, O.; de Rijke, M.; d'Aquin, M.; Dietze, S.; Drachsler, H.; Guy, M.; Herder, E.;
    Publisher: CEUR-WS
    Country: Netherlands
    Project: NWO | Modeling and Learning fro... (2300171779), NWO | SPuDisc: Searching Public... (2300176811), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702), NWO | Semantic Search in E-Disc... (2300168486)

    In this paper we present yourHistory: a Facebook application that aims to generate a tailor-made, personalized timeline of historic events, by matching a semantically enriched Facebook profile to a pool of candidate historic events extracted from DBPedia. Two aspects are central to our application: (i) semantic linking technologies backed by rich open web knowledge bases for generating semantically enriched user profiles, and (ii) semantic relatedness metrics for ranking historic events to user profiles. This paper describes the development of a Facebook application that aims to be engaging for users, whilst at the same time being a source for data that can be applied to evaluating or improving the application. We describe our Wikipedia-based semantic relatedness metric for event ranking, but also the restrictions and constraints concerning privacy-sensitive and ethical matters, around data storage and user consent. Finally, we reflect on how this type of user data can be applied for evaluating or improving both the semantic linking and event ranking methods in future work.

  • Open Access English
    Authors: 
    Huijnen, Pim; Laan, Fons; de Rijke, Maarten; Pieters, Toine; Nadamoto, A; Jatowt, A; Wierzbicki, A; Leidner, JL; Sub History and Philosophy of Science; Sub Pharmacoepidemiology; +3 more
    Country: Netherlands
    Project: NWO | Modeling and Learning fro... (2300171779), NWO | SPuDisc: Searching Public... (2300176811), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702), NWO | Semantic Search in E-Disc... (2300168486)

    Comparative historical research on the the intensity, diversity and fluidity of public discourses has been severely hampered by the extraordinary task of manually gathering and processing large sets of opinionated data in news media in different countries. At most 50,000 documents have been systematically studied in a single comparative historical project in the subject area of heredity and eugenics. Digital techniques, like the text mining tools WAHSP and BILAND we have developed in two successive demonstrator projects, are able to perform advanced forms of multi-lingual text-mining in much larger data sets of newspapers. We describe the development and use of WAHSP and BILAND to support historical discourse analysis in large digitized news media corpora. Furthermore, we argue how text mining techniques overcome the problem of traditional historical research that only documents explicitly referring to eugenics issues and debates can be incorporated. Our tools are able to provide information on ideas and notions about heredity, genetics and eugenics that circulate in discourses that are not directly related to eugenics (e.g., sport, education and economics).

  • Publication . Article . Preprint . 2013 . Embargo End Date: 01 Jan 2013
    Open Access
    Authors: 
    Zoghi, M.; Whiteson, S.; Munos, R.; de Rijke, M.;
    Publisher: arXiv
    Country: Netherlands
    Project: NWO | SPuDisc: Searching Public... (2300176811), NWO | Semantic Search in E-Disc... (2300168486), EC | LIMOSINE (288024), NWO | Modeling and Learning fro... (2300171779), NWO | Digging archaeology data:... (2300186891), NWO | Building Rich Links to En... (2300153702), EC | COMPLACS (270327)

    This paper proposes a new method for the K-armed dueling bandit problem, a variation on the regular K-armed bandit problem that offers only relative feedback about pairs of arms. Our approach extends the Upper Confidence Bound algorithm to the relative setting by using estimates of the pairwise probabilities to select a promising arm and applying Upper Confidence Bound with the winner as a benchmark. We prove a finite-time regret bound of order O(log t). In addition, our empirical results using real data from an information retrieval application show that it greatly outperforms the state of the art. Comment: 13 pages, 6 figures

  • Publication . Conference object . 2013
    Open Access English
    Authors: 
    Kenter, T.; Graus, D.; Meij, E.; de Rijke, M.;
    Publisher: Microsoft Research
    Country: Netherlands
    Project: NWO | Modeling and Learning fro... (2300171779), NWO | SPuDisc: Searching Public... (2300176811), NWO | Building Rich Links to En... (2300153702), EC | LIMOSINE (288024), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)

    Document filtering over time is applied in tasks such as tracking topics in online news or social media. We consider it a classification task, where topics of interest correspond to classes, and the feature space consists of the words associated to each class. In streaming settings the set of words associated with a concept may change. In this paper we employ a multinomial Naive Bayes classifier and perform periodic feature selection to adapt to evolving topics. We propose two ways of employing Pearson's χ2 test for feature selection and demonstrate their benefit on the TREC KBA 2012 data set. By incorporating a time-dependent function in our equations for χ2 we provide an elegant method for applying different weighting and windowing schemes. Experiments show improvements of our approach over a non-adaptive baseline, in a realistic settings with limited amounts of training data.

  • Publication . Conference object . 2013
    Open Access English
    Authors: 
    Reinanda, R.; Odijk, D.; de Rijke, M.;
    Publisher: Microsoft Research
    Country: Netherlands
    Project: NWO | SPuDisc: Searching Public... (2300176811), NWO | Modeling and Learning fro... (2300171779), NWO | Building Rich Links to En... (2300153702), EC | LIMOSINE (288024), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)

    We address the problem of entity-oriented search in the humanities and social sciences domain. We are particularly interested in retrieving entities related to a query entity and finding associations between these entities over time. Evidence from our target end users suggests that it is more informative to view these associations as dynamic phenomena that evolve over time than as static phenomena. We present work-in-progress on methods to extract these associations and their temporal extent, and discuss a way of presenting them in an exploratory search interface. This interface is intended to help users to discover interesting associations between entities over time

  • Other research product . Other ORP type . 2013
    Open Access
    Authors: 
    Reinanda, R.; Odijk, D.; de Rijke, M.;
    Publisher: TAIA '13
    Country: Netherlands
    Project: NWO | SPuDisc: Searching Public... (2300176811), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486), NWO | Modeling and Learning fro... (2300171779), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702)
  • Publication . Part of book or chapter of book . 2012
    Open Access English
    Authors: 
    de Rijke, M.; Jijkoun, V.; Laan, F.; Weerkamp, W.; Ackermans, P.; Geleijnse, G.; Spyns, P.; Odijk, J.;
    Country: Netherlands
    Project: NWO | Building Rich Links to En... (2300153702), EC | LIMOSINE (288024), NWO | Content-based Literature ... (2300152116), NWO | DutchSemCor: 1 million te... (2300154091), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)

    In order to use a sentiment extraction system for a media analysis problem, a system would have to be able to determine which of the extracted sentiments are relevant, i.e., it would not only have to identify targets of extracted sentiments, but also decide which targets are relevant for the topic at hand.

  • Open Access English
    Authors: 
    de Rijke, Maarten; Jijkoun, Valentin; Laan, Fons; Weerkamp, Wouter; Ackermans, Paul; Geleijnse, Gijs;
    Publisher: Springer Berlin Heidelberg
    Project: NWO | Content-based Literature ... (2300152116), NWO | DutchSemCor: 1 million te... (2300154091), EC | LIMOSINE (288024), NWO | Building Rich Links to En... (2300153702), EC | PROMISE (258191), NWO | Semantic Search in E-Disc... (2300168486)