References of "Schommer, Christoph 50003041"
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See detailA Bilingual Study for Personalized Sentiment Model PERSEUS
Guo, Siwen UL; Schommer, Christoph UL

Scientific Conference (2018, September 10)

This paper investigates the significance of analyzing language preferences in personalized sentiment analysis. Motivated by the considerable amount of text generated by multilingual speakers on social ... [more ▼]

This paper investigates the significance of analyzing language preferences in personalized sentiment analysis. Motivated by the considerable amount of text generated by multilingual speakers on social platforms, we focus on constructing a single model that is able to analyze sentiments in a multilingual environment. In particular, Twitter texts are used in this research where the choice of language can be switched at a message-, sentence-, word- or topic-level. To represent and analyze the text, we extract concepts and main topics from the text and apply a recurrent neural network with attention mechanism in order to learn the relation between the lexical choices and the opinions of each sentiment holder. The personalized sentiment model PERSEUS is applied as the central structure of this research. Moreover, a language index is added to each concept to enable multilingual analysis, which provides a solution for analyzing code-switching in the text as well. In this work, English and German are chosen for a pilot study, and an artificial corpus is created to evaluate the situation with multilingual speakers. [less ▲]

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See detailA Dynamic Associative Memory for Distant Reading
Kamlovskaya, Ekaterina UL; Schommer, Christoph UL; Sirajzade, Joshgun UL

in International Conference on Artificial Intelligence Humanities, Book of Abstracts (2018, August 16)

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See detailMind and Language. AI in an Example of Similar Patterns of Luxembourgish Language
Sirajzade, Joshgun UL; Schommer, Christoph UL

in International Conference on Artificial Intelligence Humanities, Book of Abstracts (2018, August 16)

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See detailPsychological, cognitive factors and contextual influences in pain and pain-related suffering as revealed by a combined qualitative and quantitative assessment approach
Bustan S; Gonzalez-Roldan AM; Schommer, Christoph UL et al

in PLoS ONE (2018)

Previous psychophysiological research suggests that pain measurement needs to go beyond the assessment of Pain Intensity and Unpleasantness by adding the evaluation of Pain-Related Suffering. Based on ... [more ▼]

Previous psychophysiological research suggests that pain measurement needs to go beyond the assessment of Pain Intensity and Unpleasantness by adding the evaluation of Pain-Related Suffering. Based on this three-dimensional approach, we attempted to elucidate who is more likely to suffer by identifying reasons that may lead individuals to report Pain and Pain-Related Suffering more than others. A sample of 24 healthy participants (age range 18±33) underwent four different sessions involving the evaluation of experimentally induced phasic and tonic pain. We applied two decision tree models to identify variables (selected from psychological questionnaires regarding pain and descriptors from post-session interviews) that provided a qualitative characterization of the degrees of Pain Intensity, Unpleasantness and Suffering and assessed the respective impact of contextual influences. The overall classification accuracy of the decision trees was 75% for Intensity, 77% for Unpleasantness and 78% for Pain-Related Suffering. The reporting of suffering was predominantly associated with fear of pain and active cognitive coping strategies, pain intensity with bodily competence conveying strength and resistance and unpleasantness with the degree of fear of pain and catastrophizing. These results indicate that the appraisal of the three pain dimensions was largely determined by stable psychological constructs. They also suggest that individuals manifesting higher active coping strategies may suffer less despite enhanced pain and those who fear pain may suffer even under low pain. The second decision tree model revealed that suffering did not depend on pain alone, but that the complex rating-related decision making can be shifted by situational factors (context, emotional and cognitive). The impact of coping and fear of pain on individual Pain-Related Suffering may highlight the importance of improving cognitive coping strategies in clinical settings. [less ▲]

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See detailProceedings - 2017 ILILAS Distinguished Lectures
Bouvry, Pascal UL; Bisdorff, Raymond; Schommer, Christoph UL et al

Report (2018)

The Proceedings summarizes the 12 lectures that have taken place within the ILIAS Dinstguished Lecture series 2017. It contains a brief abstract of the talks as well as some additional information about ... [more ▼]

The Proceedings summarizes the 12 lectures that have taken place within the ILIAS Dinstguished Lecture series 2017. It contains a brief abstract of the talks as well as some additional information about each speaker. [less ▲]

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See detailPERSEUS: A Personalization Framework for Sentiment Categorization with Recurrent Neural Network
Guo, Siwen UL; Höhn, Sviatlana; Xu, Feiyu et al

in International Conference on Agents and Artificial Intelligence , Funchal 16-18 January 2018 (2018, January)

This paper introduces the personalization framework PERSEUS in order to investigate the impact of individuality in sentiment categorization by looking into the past. The existence of diversity between ... [more ▼]

This paper introduces the personalization framework PERSEUS in order to investigate the impact of individuality in sentiment categorization by looking into the past. The existence of diversity between individuals and certain consistency in each individual is the cornerstone of the framework. We focus on relations between documents for user-sensitive predictions. Individual’s lexical choices act as indicators for individuality, thus we use a concept-based system which utilizes neural networks to embed concepts and associated topics in text. Furthermore, a recurrent neural network is used to memorize the history of user’s opinions, to discover user-topic dependence, and to detect implicit relations between users. PERSEUS also offers a solution for data sparsity. At the first stage, we show the benefit of inquiring a user-specified system. Improvements in performance experimented on a combined Twitter dataset are shown over generalized models. PERSEUS can be used in addition to such generalized systems to enhance the understanding of user’s opinions. [less ▲]

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See detailEmbedding of the Personalized Sentiment Engine PERSEUS in an Artificial Companion
Guo, Siwen UL; Schommer, Christoph UL

in International Conference on Companion Technology, Ulm 11-13 September 2017 (2017, September)

The term Artificial Companion has originally been introduced by Y. Wilks [1] as “...an intelligent and helpful cognitive agent, which appears to know its owner and their habits, chats to them and diverts ... [more ▼]

The term Artificial Companion has originally been introduced by Y. Wilks [1] as “...an intelligent and helpful cognitive agent, which appears to know its owner and their habits, chats to them and diverts them, assists them with simple tasks. . . ”. To serve the users’ interests by considering a personal knowledge is, furthermore, demanded. The following position paper takes this request as motivation for the embedding of the PERSEUS system, which is a personalized sentiment framework based on a Deep Learning approach. We discuss how such an embedding with a group of users should be realized and why the utilization of PERSEUS is beneficial. [less ▲]

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See detailProceedings of the 2nd International Workshop on Exploring Old Maps
van Dijk, Thomas; Schommer, Christoph UL

Book published by University of Würzburg - 2nd (2017)

Many libraries own an extensive collection of historical maps. Beside their value as historical objects, these maps are an important source of information for researchers in various scientific disciplines ... [more ▼]

Many libraries own an extensive collection of historical maps. Beside their value as historical objects, these maps are an important source of information for researchers in various scientific disciplines. This ranges from the actual history of cartography and general history to the geographic and social sciences. With the progressing digitisation of libraries and archives, these maps become more easily available to a larger public. A basic level of digitisation consists of scanned bitmap images, tagged with some basic bibliographic information such as title, author and year of production. In order to make the maps more accessible, further metadata describing the contained information is desirable. This would enable more user-friendly interfaces, relevant queries of a database, and automatic analyses. This international workshop provides a forum for the communication of results that may be useful to the community. Researchers and practitioners of many areas working on unlocking the content of old maps have contributed to this year’s program — humanities scholars, developers, computer and information scientists and map enthusiasts. [less ▲]

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See detailQ&A with Data Scientists: Christopher Schommer
Schommer, Christoph UL

in Operational Database Management Systems (2017)

Interviews with Data Scientists; see: http://www.odbms.org/2017/01/qa-with-data-scientists-christopher-schommer/

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See detailRAT 2.0
Höhn, Winfried UL; Schommer, Christoph UL

in Digital Humanities 2017: Conference Abstracts (2017)

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See detailGeoreferencing of Place Markers in Digitized Early Maps by Using Similar Maps as Data Source
Höhn, Winfried UL; Schommer, Christoph UL

in Digital Humanities 2017: Conference Abstracts (2017)

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See detailFacteurs psychologiques, cognitifs et les influences contextuelles dans la douleur et la souffrance liée à la douleur
Bustan, Smadar; Gonzalez-Roldan, Ana Maria; Schommer, Christoph UL et al

Poster (2016, November)

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See detailAnnotating and Georeferencing of Digitized Early Maps
Höhn, Winfried UL; Schommer, Christoph UL

Poster (2016, July)

Original early maps are usually only accessible for a small group of researchers and librarians because they are very old and sensitive, and could be easily destroyed. However, they are a valuable ... [more ▼]

Original early maps are usually only accessible for a small group of researchers and librarians because they are very old and sensitive, and could be easily destroyed. However, they are a valuable knowledge source for historical research, because they are also political and cultural evidences of its time. In the age of Digital Humanities, online access and information search in digitized historical documents and early maps allows people from all over the world to work with such artefacts of cultural heritage. However, the digitization solely generates images of the artefacts without any access to the semantics of the documents. [less ▲]

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See detailProceedings International Workshop Exploring Old Maps 2016
van Dijk, Thomas; Schommer, Christoph UL

Book published by University of Luxembourg (2016)

Many libraries own an extensive collection of historical maps. Beside their value as historical objects, these maps are an important source of information for researchers in various scientific disciplines ... [more ▼]

Many libraries own an extensive collection of historical maps. Beside their value as historical objects, these maps are an important source of information for researchers in various scientific disciplines. This ranges from the actual history of cartography and general history to the geographic and social sciences. With the progressing digitisation of libraries and archives, these maps become more easily available to a larger public. A basic level of digitisation consists of scanned bitmap images, tagged with some basic bibliographic information such as title, author and year of production. In order to make the maps more accessible, further metadata describing the contained information is desirable. This would enable more user-friendly interfaces, relevant queries of a database, and automatic analyses. The International Workshop on Exploring Old Maps provides a forum for the communication of results that may be useful to the community. Researchers and practitioners of many areas working on unlocking the content of old maps have contributed to this year’s program - humanities scholars, developers, computer and information scientists as well as librarians, archivists and curators. [less ▲]

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See detailRAT: A Referencing and Annotation Tool for Digitized Early Maps
Höhn, Winfried UL; Schommer, Christoph UL

Scientific Conference (2016, June)

RAT is designed to support users in identifying place markers in digitised early maps and to link these place markers to modern maps. RAT facilitates a geo-referencing by suggesting the most likely modern ... [more ▼]

RAT is designed to support users in identifying place markers in digitised early maps and to link these place markers to modern maps. RAT facilitates a geo-referencing by suggesting the most likely modern places based on an estimated mapping and a phonetic search for place names. [less ▲]

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See detailInteraction Profiles for an Artificial Conversational Companion
Höhn, Sviatlana UL; Busemann, Stephan; Max, Charles UL et al

Scientific Conference (2015, September)

Using Artificial Companions for tasks requiring long-term interaction like language learning or coaching can be approached by creating local computational models for particular interaction structures, and ... [more ▼]

Using Artificial Companions for tasks requiring long-term interaction like language learning or coaching can be approached by creating local computational models for particular interaction structures, and models reflecting changes in interaction over time. An Artificial Conversational Companion (ACC) that helps to practice conversation in a foreign language is expected to play the role of a language expert in conversation. We apply methods of Conversation Analysis to obtain data- driven models of interaction profiles for language experts and language novices from a corpus of instant messaging based dialogues between native speakers of German and advanced learners of German as a foreign language. We show different ways how the artificial agent can simulate ”doing being expert” in conversation and promote learning. [less ▲]

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See detailSentiment Barometer in Financial News
Schommer, Christoph UL

Report (2014)

This booklet is a collection of project reports written by graduate students, who have participated the course "Machine Learning" in Winter Term 2013/14. Here, we have concerned Financial News Documents ... [more ▼]

This booklet is a collection of project reports written by graduate students, who have participated the course "Machine Learning" in Winter Term 2013/14. Here, we have concerned Financial News Documents regarding the Irish Financial Crisis in the years of 2009 - 2013. We have studied different forms of sentiments, for example with StoryTakes, Alerts, Headlines, authors, and others. [less ▲]

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See detailFinding Outliers in Satellite Patterns by Learning Pattern Identities
Bouleau, Fabien; Schommer, Christoph UL

in Filipe, Joacquim; Fred, Ana (Eds.) Proceedings "6th International Conference on Agents an Artificial Intelligence" (2014, January)

Spacecrafts provide a large set of on-board components information such as their temperature, power and pressure. This information is constantly monitored by engineers, who capture the outliers and ... [more ▼]

Spacecrafts provide a large set of on-board components information such as their temperature, power and pressure. This information is constantly monitored by engineers, who capture the outliers and determine whether the situation is abnormal or not. However, due to the large quantity of information, only a small part of the data is being processed or used to perform anomaly prediction. A common accepted research concept for anomaly prediction as described in literature yields on using projections, based on probabilities, estimated on learned patterns from the past (Fujimaki et al., 2005) and data mining methods to enhance the conventional diagnosis approach (Li et al., 2010). Most of them conclude on the need to build a status vector. We propose an algorithm for efficient outlier detection that builds an identity chart of the patterns using the past data based on their curve fitting information. It detects the functional units of the patterns without apriori knowledge with the intent to learn its structure and to reconstruct the sequence of events described by the signal. On top of statistical elements, each pattern is allotted a characteristics chart. This pattern identity enables fast pattern matching across the data. The extracted features allow classification with regular clustering methods like support vector machines (SVM). The algorithm has been tested and evaluated using real satellite telemetry data. The outcome and performance show promising results for faster anomaly prediction. [less ▲]

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See detailA Hidden Markov Model to detect relevance in nancial documents based on on/off topics
Kampas, Dimitrios UL; Schommer, Christoph UL; Sorger, Ulrich UL

in European Conference on Data Analysis (2014)

Automated text classification has gained a significant attention since a vast amount of documents in digital forms are widespread and continuously increasing. Most of the standard classification posit the ... [more ▼]

Automated text classification has gained a significant attention since a vast amount of documents in digital forms are widespread and continuously increasing. Most of the standard classification posit the independence of the terms-features in document, which is unrealistic considering the sophisticated structure of the language. Our research concerns the discovery of relevance in documents, which adequately refers to a sufficient number of thematic themes (or topics) that are either `on' or `off'. `On topics' are semantically close with a domain specific discourse, whereas `Off topics' are not considered to be on documents. As a rather promising approach, we have modelled a stochastic process for term sequences, where each term is conditionally dependent of its preceeding terms. Hidden Markov Models hereby provide a reliable potential to incorporate language and domain dependencies for a classification. Terms are deterministically associated with classes to improve the probability estimates for the infrequent words. In the paper presentation, we demonstrate our approach and motivate its eligibility by the exploration of annotated Thomson Reuters news documents; in particular, the `on topic' documents discourse the monetary policy of Federal Reserves. We estimate the transition and emission probabilities of our model on a training set of both on and off topic documents and evaluate the accuracy of our approach using 10-fold cross validation. This work is part of the interdisciplinary research project ESCAPE, which is funded by the Fonds National de la Recherche. We kindly thank our colleagues from the Dept. of Finance for their support. [less ▲]

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See detailNews Representation with Multi-Word Features
Minev, Mihail UL; Schommer, Christoph UL

in Proceedings ECDA (2013, July)

Detailed reference viewed: 60 (19 UL)