@InProceedings{nandzik10contentus,
  author = 	 {Jan Nandzik and Andreas He{\ss} and Jan Hannemann and Nicolas Flores-Herr and Klaus Bossert},
  title = 	 {CONTENTUS - towards semantic multi-media libraries},
  booktitle = {World Library and Information Congress: 76th IFLA General Conference and Assembly},
  year = 	 {2010},
  address = 	 {Gothenburg, Sweden},
  month = 	 {August},
  url = "http://www.andreas-hess.info/publications/149-nandzik-en.pdf",
  abstract ="The ever-growing amount of content and knowledge published online makes it possible for libraries to complement their own data and to present their collections in novel ways. Conceptually related information can be semantically linked so that users may benefit from richer data collections and novel search possibilities that capitalize on the inherent relationships between media, local metadata and external information sources. This paper presents potential solutions for the fundamental challenges of integrating heterogeneous data sources and providing innovative semantic search approaches, as they are developed for libraries and multimedia archives within the CONTENTUS project."
}

@InProceedings{dopichaj09stealing,
  author = 	 {Philipp Dopichaj and Andre Skusa and Andreas He{\ss}},
  title = 	 {Stealing Anchors to Link the Wiki},
  booktitle = {Advances in Focused Retrieval, 7th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2008, Dagstuhl Castle, Germany, December 15-18, 2008. Revised and Selected Papers},
  year = 	 {2009},
  address = 	 {Schloss Dagstuhl, Germany},
  month = 	 {December},
  url = "http://www.andreas-hess.info/publications/dopichaj-inex08.pdf"
}

@InBook{maass09markt,
  author = 	 {Christian Maa{\ss} and Andre Skusa and Andreas He{\ss} and Gotthard Pietsch},
  title = 	 {Handbuch Internet-Suchmaschinen},
  chapter = 	 {Der Markt für Internet-Suchmaschinen},
  publisher = 	 {AKA Verlag},
  year = 	 {2009},
  address = 	 {Heidelberg},
  pages = 	 {3--17},
}

@InProceedings{hess08multi,
  author = 	 {Andreas He{\ss} and Philipp Dopichaj and Christian Maa{\ss}},
  title = 	 {Multi-Value Classification of Very Short Texts},
  booktitle = {31st Annual German
  Conference on Artificial Intelligence (KI 2008)},
  year = 	 {2008},
  address = 	 {Kaiserslautern, Germany},
  month = 	 {September},
  url = "http://www.andreas-hess.info/publications/hess-ki08.pdf",
  abstract ="We introduce a new stacking-like approach for
multi-value classification. We apply this classification scheme using
Naive Bayes and Rocchio classifiers on the well-known Reuters
dataset. We use part-of-speech tagging for stopword removal. We show
that our setup performs just as well as other approaches that use the
full article text even though we only classify headlines. Finally, we
apply a Rocchio classifier on a dataset from a Web 2.0-site and show
that it is suitable for semi-automated labelling (often called
tagging) of short texts and is faster than other approaches."
}

@InProceedings{dierick08playful,
  author = 	 {Francis Dierick and Philipp Dopichaj and Uwe Fleischer and Andreas He\{ss} and Andre Skusa and Christian Maa\{ss}},
  title = 	 {Playful Validation of Automatically Extracted Data},
  booktitle = {Mensch und Computer 2008, Workshop Nutzerinteraktion im Social Semantic Web},
  year = 	 {2008},
  url = "http://www.andreas-hess.info/publications/dierick-muc08.pdf"
}

@InProceedings{hess08from,
  author = 	 {Andreas He{\ss} and Christian Maa{\ss} and Francis Dierick},
  title = 	 {From Web 2.0 to Semantic Web: A Semi-Automated Approach},
  booktitle = {ESWC 08 Workshop on Collective Semantics: Collective Intelligence and the Semantic Web (CISWeb 2008)},
  year = 	 {2008},
  address = 	 {Tenerife, Spain},
  month = 	 {June},
  url = "http://www.andreas-hess.info/publications/hess-cisweb08.pdf",
  abstract ="Web 2.0 and Semantic Web are regarded as two complementary paradigms that will probably converge in the future. However, whereas the Semantic Web is an established field of research, there has been little analysis devoted to Web 2.0 applications. For this reason it remains unclear how the advantages of both paradigms could be merged. In this paper we make three contributions in this direction. First, we discuss why merging Web 2.0 and the Semantic Web is beneficial and propose five approaches. Second, we show that (semi-) automated tagging of content improves the quality of annotations. Third, we present an automatic approach for improving the tag quality by using duplicate detection techniques. We verify our approach on a large-scale data set from the social search service Lycos IQ."
}

@InProceedings{graefe07alternative,
  author = 	 {Gernot Graefe and Christian Maa{\ss} and Andreas He{\ss}},
  title = 	 {Alternative Searching
  Services: Seven Theses on the Importance of Social
  Bookmarking},
  url = "http://www.andreas-hess.info/publications/graefe-sabre07.pdf",
  booktitle = {Software, Agents and Services for Business, Research and E-Sciences — Conference on Social Semantic Web
(SABRE/CSSW 2007)},
  year = 	 {2007},
  address = 	 {Leipzig, Germany},
  abstract = "In recent years social bookmark systems like del.icio.us or Furl have become increasingly popular. These systems sometimes are regarded as alternatives to algorithmic search engines like Google. In this paper we develop seven theses on the potential of these systems in order to establish a conceptual basis for future research in this area. Thereby it becomes clear that social bookmarking systems complement rather than threaten algorithmic search engines."
}

@InProceedings{hess06iterative,
  author = 	 {Andreas He{\ss}},
  title = 	 {An Iterative Algorithm for Ontology Mapping Capable of Using Training Data},
  booktitle = {Proceedings of the 3rd European Semantic Web Conference
(ESWC 2006)},
  year = 	 2006,
  address = 	 {Budva, Montenegro},
  url = "http://www.andreas-hess.info/publications/hess-eswc06.pdf",
  abstract = "We present a new iterative algorithm for ontology mapping where we combine standard string distance metrics with a structural similarity measure that is based on a vector representation. After all pairwise similarities between concepts have been calculated we apply well-known graph algorithms to obtain an optimal matching. Our algorithm is also capable of using existing mappings to a third ontology as training data to improve accuracy. We compare the performance of our algorithm with the performance of other alignment algorithms and show that our algorithm can compete well against the current state-of-the-art."
}


@PhdThesis{hess05supervised,
  author = 	 {Andreas He{\ss}},
  title = 	 {Supervised and Unsupervised Ensemble Learning for the Semantic Web},
  school = 	 {School of Computer Science and Informatics, University College Dublin},
  month = {February},
  year = 	 {2006},
  address = 	 {Dublin, Ireland},
  url = "http://www.andreas-hess.info/publications/hess-thesis.pdf",
  abstract = "The World Wide Web offers an ocean of information and services for everyone, and many of us rely on it on a daily basis. One of the reasons for the Web's success is that the threshold for creating content on the Web was always very low, because comfortable and easy to use HTML editors are available. However, today's Web is limited by the fact that it is machine-readable, but not machine-understandable. The Semantic Web promises a solution to this problem by adding explicit semantics with the goal of making the Web machine-understandable by using description logics and ontologies. However, the threshold for creating this extra markup is very high, and no comfortable tools exist at present. The goal of this work is to develop such tools. Machine Learning techniques have been used in literature for various classification tasks. The central claim of this thesis is that such algorithms, supervised and unsupervised, can be used for this purpose."
}

@InCollection{hess06dublin,
  author = 	 {Andreas He{\ss}},
  title = 	 {The Dublin Algorithm for Ontology Alignment},
  booktitle = 	 {Deliverable 2.2.4: Alignment implementation and benchmarking results},
  pages = 	 {7--10},
  year = 	 {2006},
  editor = 	 {Heiner Stuckenschmidt et al.},
  publisher = 	 {Knowledge Web Network of Excellence},
  chapter = 	 {1},
  month = 	 {February},
  url = "http://knowledgeweb.semanticweb.org/semanticportal/deliverables/D2.2.4.pdf"
}

@InProceedings{khoussainov05ensembles,
  author = 	 {Rinat Khoussainov and Andreas He{\ss} and Nicholas Kushmerick},
  title = 	 {Ensembles of Biased Classifiers},
  booktitle = {Proceedings of the 22nd International Conference on Machine Learning (ICML 2005)},
  year = 	 {2005},
  address = 	 {Bonn, Germany},
  url = "http://www.andreas-hess.info/publications/khoussainov-icml05.pdf",
  abstract = "We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high precision on instances from a single class (as opposed to, for example, boosting, where the ensemble members are biased to maximise accuracy over a subset of instances from all classes). Second, the ensemble members' voting weights are assigned so that certain pairs of biased classifiers outweigh the rest of the ensemble, if their predictions agree. Our experiments demonstrate that Triskel often outperforms boosting, in terms of both accuracy and training time. We also present an ROC analysis, which shows that Triskel's iterative structure corresponds to a sequence of nested ROC spaces. The analysis predicts that Triskel works best when there are concavities in the ROC curves; this prediction agrees with our empirical results."
}

@InProceedings{hess05ensemble,
  author = 		 {Andreas He{\ss} and Rinat Khoussainov and Nicholas Kushmerick},
  title = 		 {Ensemble Learning with Biased Classifiers: The Triskel Algorithm},
  booktitle = 		 {Proceedings of the 6th International Workshop on Multiple Classifier Systems},
  year =                 {2005},
  address =              {Monterey Bay, California, USA},
  url = "http://www.andreas-hess.info/publications/hess-mcs05.pdf"
}

@InProceedings{hess05machine,
  author = 		 {Andreas He{\ss} and Eddie Johnston and Nicholas Kushmerick},
  title = 		 {Machine Learning Techniques for Annotating Semantic Web Services},
  booktitle = 		 {Proceedings of the Dagstuhl Seminar on Machine Learning for the Semantic Web},
  year =                 {2005},
  address =              {Schloss Dagstuhl, Germany},
  url = "http://www.andreas-hess.info/publications/hess-dagstuhl-mlsw-2005.pdf"
}

@InProceedings{hess04assam,
  author = 		 {Andreas He{\ss} and Eddie Johnston and Nicholas Kushmerick},
  title = 		 {ASSAM: A Tool for Semi-Automatically Annotating Semantic Web Services},
  booktitle = 		 {Proceedings of the 3rd International Semantic Web Conference (ISWC 2004)},
  year =                 {2004},
  address =              {Hiroshima, Japan},
  url = "http://www.andreas-hess.info/publications/hess-iswc04.pdf",
  abstract = " The Semantic Web Services vision requires that each service be annotated with semantic metadata. Manually creating such metadata is tedious and error-prone, and many software engineers, accustomed to tools that automatically generate WSDL, might not want to invest the additional effort. We therefore propose ASSAM, a tool that assists a user in creating semantic metadata for Web Services. ASSAM is intended for service consumers who want to integrate a number of services and therefore must annotate them according to some shared ontology. ASSAM is also relevant for service producers who have deployed a Web Service and want to make it compatible with an existing ontology. ASSAM's capabilities to automatically create semantic metadata are supported by two machine learning algorithms. First, we have developed an iterative relational classification algorithm for semantically classifying Web Services, their operations, and input and output messages. Second, to aggregate the data returned by multiple semantically related Web Services, we have developed a schema mapping algorithm that is based on an ensemble of string distance metrics."
}

@InProceedings{hess04iterative,
  author = 		 {Andreas He{\ss} and Nicholas Kushmerick},
  title = 		 {Iterative Ensemble Classification for Relational Data: A Case
Study of Semantic Web Services},
  booktitle =    {Proceedings of the 15th European Conference on Machine Learning},
  year =         {2004},
  address =      {Pisa, Italy},
  url = "http://www.andreas-hess.info/publications/hess-ecml04.pdf",
  abstract = "For the classification of relational data, iterative algorithms that feed back predicted labels of associated objects have been used. In this paper we show two extensions to existing approaches. First, we propose to use two separate classifiers for the intrinsic and the relational (extrinsic) attributes and vote their predictions. Second, we introduce a new way of exploiting the relational structure. When the extrinsic attributes alone are not sufficient to make a prediction, we train specialised classifiers on the intrinsic features and use the extrinsic features as a selector. We apply these techniques to the task of semi-automated Web Service annotation, a task with a rich relational structure."
}

@InProceedings{hess04semi,
  author = 		 {Andreas He{\ss} and Eddie Johnston and Nicholas Kushmerick},
  title = 		 {Semi-Automatically Annotating Semantic Web Services (Extended Abstract)},
  booktitle = {30th International Conference on Very Large Data Bases, Workshop Information Integration on the Web},
  year = 	 {2004},
  address = 	 {Toronto, Canada},
  url = "http://www.andreas-hess.info/publications/hess-vldb04-iiw.pdf"
}

@InProceedings{hess04machine,
  author = 	 {Andreas He{\ss} and Nicholas Kushmerick},
  title = 	 {Machine Learning for Annotating Semantic Web Services},
  booktitle = {{AAAI} Spring Symposium on Semantic Web Services},
  year = 	 {2004},
  address = 	 {Palo Alto, California, USA},
  url = "http://www.andreas-hess.info/publications/hess-aaai04.pdf"
}


@InProceedings{hess03learning,
  author = 	 {Andreas He{\ss} and Nicholas Kushmerick},
  title = 	 {Learning to Attach Semantic Metadata to Web Services},
  booktitle =    {Proceedings of the 2nd International Semantic Web Conference},
  pages = 	 {258--273},
  year = 	 {2003},
  editor = 	 {Dieter Fensel and Katia Sycara and John Mylopoulos},
  number = 	 {2870},
  series = 	 {Lecture Notes in Computer Science},
  address = 	 {Sanibel Island, Florida, USA},
  publisher = {Springer Verlag},
  url = "http://www.andreas-hess.info/publications/hess-iswc03.pdf",
  abstract = "Emerging Web standards promise a network of heterogeneous yet interoperable Web Services. Web Services would greatly simplify the development of many kinds of data integration and knowledge management applications. Unfortunately, this vision requires that services describe themselves with large amounts of semantic metadata "glue". We explore a variety of machine learning techniques to semi-automatically create such metadata."
}

@InProceedings{hess03automatically,
  author = 		 {Andreas He{\ss} and Nicholas Kushmerick},
  title = 		 {Automatically Attaching Semantic Metadata to Web Services},
  booktitle = {International Joint Conference on Artificial Intelligence, Workshop Information Integration on the Web},
  year = 	 {2003},
  address = 	 {Acapulco, Mexico},
  url = "http://www.andreas-hess.info/publications/hess-ijcai03-iiw.pdf"
}

@MastersThesis{hess01themenextraktion,
  author = 		 {Andreas He{\ss}},
  title = 		 {Themenextraktion aus Semantischen Netzen},
  school = 		 {Fachhochschule Darmstadt, University of Applied Science},
  year = 		 {2001},
  address = 	 {Darmstadt, Germany},
  url = "http://www.andreas-hess.info/publications/Themenextraktion.ps.gz"
}