Multilingual Ontology-based User Profile Enrichment Ernesto William De Luca, Till Plumbaum, Jérôme Kunegis, Sahin Albayrak DAI Lab, Technische Universität Berlin Ernst-Reuter-Platz 7, 10587 Berlin, Germany {ernesto.deluca, till.plumbaum, jerome.kunegis, sahin.albayrak}@dai-labor.de ABSTRACT vocabulary that is not contained in the documents, known In this paper, we discuss the possibility of enriching user pro- as the paraphrase problem. files with multilingual information. Nowadays, the English Multilingual Retrieval. When working in a multilingual language is the de facto standard language of commerce and environment, words have to be disambiguated both in the science, however users can speak and interact also in other native and in the other languages. In this case the com- languages. This brings up the need of enriching the user pro- bination of multilingual text retrieval and word sense dis- files with multilingual information. Therefore, we propose ambiguation (WSD) approaches is crucial [2]. In order to to combine ontology-based user modeling with the informa- retrieve the same concept in different languages, some re- tion included in the RDF/OWL EuroWordNet hierarchy. lations between the searched concept and its translations In this way, we can personalize retrieval results according to have to be built. WSD is used to convert relations between user preferences, filtering relevant information taking into words into relations between concepts; sense disambigua- account the multilingual background of the user. tion can be acquired for words, but it is more difficult for documents. To have accurate WSD, we need a larger cov- erage of semantic and linguistic knowledge than is available Categories and Subject Descriptors in current lexical resources. H.3.1 [Information Storage and Retrieval]: Content Because we focus on multilingual concepts, we decided to Analysis and Indexing use EuroWordNet [6], a variant of the most well-known avail- able lexical database WordNet. In previous work, we ex- tended the RDF/OWL WordNet representation [5] for mul- General Terms tilingualism, leading to our own RDF/OWL EuroWordNet RDF/OWL, Web 2.0, Multilingualism, EuroWordNet representation [3]. Ontology-based User Modeling. With the advent of the Web 2.0 and the growing impact of the Internet on our ev- Keywords ery day life, people start to use more and more different web Multilingual Semantic Web, User Modeling applications. They manage their bookmarks in social book- marking systems, communicate with friends on Facebook1 and use services like Twitter2 to express personal opinions 1. INTRODUCTION and interests. Thereby, they generate and distribute per- At present most of the demand for text retrieval is well sonal and social information like interests, preferences and satisfied by monolingual systems, because the English lan- goals [4]. This distributed and heterogeneous corpus of user guage is the de facto standard language of commerce and information, stored in the user model (UM) of each applica- science. However, there is a wide variety of circumstances in tion, is a valuable source of knowledge for adaptive systems which a reader might find multilingual retrieval techniques like information filtering services. These systems can utilize useful. Being able to read a document in a foreign language such knowledge for personalizing search results, recommend does not always imply that a person can formulate appropri- products or adapting the user interface to user preferences. ate queries in that language as well. Furthermore, dealing Adaptive systems are highly needed, because the amount of with polysemic words seems to be more difficult in multilin- information available on the Web is increasing constantly, re- gual than in monolingual retrieval tasks. quiring more and more effort to be adequately managed by Every text retrieval approach has two basic components: the users. Therefore, these systems need more and more in- the first for representing texts (queries and documents) and formation about users interests, preferences, needs and goals the other for their comparison. This automated process is and as precise as possible. However, this personal and so- successful when its results are similar to those produced by cial information stored in the distributed UMs usually exists human comparison between queries and documents. Queries in different languages due to the fact that we communicate and documents often differ from its length however. While with friends all over the world. Also, today’s adaptive sys- the query is often quite short, documents might be up to tems are usually part of web applications and typically only hundreds of pages long. Moreover, users frequently adopt a have access to the information stored in that specific ap- Copyright is held by the author/owner(s). 1 WWW2010, April 26-30, 2010, Raleigh, North Carolina. http://www.facebook.com/ 2 . http://twitter.com/ 41 Aggregated Profile plication. Therefore, we enhance the user model aggrega- Attrib ute Attrib ute gaan User Models tion process by adding valuable and important meta-data !"#$%&' Attrib move drive rijden ute berijd which leads to better user models and thus to better adap- ride en Interlingual tive systems. For this reason, we propose a combination of has !"#$%&( Attrib ute Index RDF/OWL EuroWordNet within ontology-based aggrega- Attrib Attrib Attrib Attrib Attrib condu icir guidare !"#$%&) tion techniques. ute ute ute ute ute caval cabal care gar mover andare Attrib Attrib ute ute 2. PROPOSED SEMANTIC RDF/OWL EuroWordNet USER MODELING AGGREGATION Figure 1: Integrating semantic knowledge about RDF/OWL EuroWordNet opens new possibilities for over- multilingual dependencies with the information coming the problem of language heterogeneity in different stored in the user models. user models and thus allows a better user modeling aggre- gation. Therefore, we propose an ontology-based user mod- elling approach that combines mediator techniques to aggre- To use the information contained in RDF/OWL Euro- gate user models from different applications and utilize the WordNet, we developed a framework that allows us to de- EuroWordNet information to handle the multilingual infor- fine several mediators that take the information from user mation in the models. Based on this idea, we define some models and trigger different sources in the Semantic Web requirements that we have to fulfill. for more information. These mediators are specialized com- Requirement 1: Ontology-based profile aggregation. We ponents that read a user model and collect additional data need an approach to aggregate information that is both ap- from an external source. plication independent and application overarching. This re- quires a solution that allows us to semantically define rela- 4. CONCLUSION tions and coherences between different attributes of differ- In this paper, we presented the possibility of enriching ent UMs. The linked attributes must be easily accessible by user profiles with information included in the RDF/OWL applications such as recommender and information filtering EuroWordNet hierarchy to better filter results during the systems. In addition, similarity must be expressed in these search process. This aggregated information can be used in defined relations. our multilingual semantic information retrieval system that Requirement 2: Integrating semantic knowledge. A so- has been described in more details in [2]. In this work, we lution to handle the multilingual information for enriching have shown that we can handle the high heterogeneity of user profiles is needed. Hence, we introduce a method to distributed data, especially concerning multilingual hetero- incorporate information from semantic data sources such as geneity, using aggregated user profiles that have been en- EuroWordNet and to aggregate complete profile informa- riched with information contained in the RDF/OWL Euro- tion. We decided to use an ontology as the conceptual ba- WordNet representation. This gives us the possibility to sis of our approach to meet the first requirement explained personalize retrieval results according to user preferences, above. Therefore a meta-ontology is used to link attributes filtering relevant information taking into account the multi- of different UMs that contain equal or similar content. lingual background of the user. The definition of a meta-model based on the meta-ontology can be divided into two steps. First, we define a concrete meta-model for a specific domain we want to work with, such 5. REFERENCES as music, movies or personal information. The meta-model [1] Shlomo Berkovsky, Tsvi Kuflik, and Francesco Ricci. can be an already existing model, like FOAF3 or a pro- Mediation of user models for enhanced personalization prietary model that only certain applications understand. in recommender systems. User Modeling and Next, we decribe how to connect multilingual attribute in- User-Adapted Interaction, 18(3):245–286, 2008. formation stored in different user models. [2] Ernesto William De Luca. Semantic Support in Multilingual Text Retrieval. Shaker Verlag, Aachen, 3. MULTILINGUAL ONTOLOGY-BASED Germany, 2008. [3] Ernesto William De Luca, Martin Eul, and Andreas AGGREGATION Nürnberger. Converting EuroWordNet in OWL and To enrich the user model with multilingual information, as extending it with domain ontologies. In Proc. Workshop described above, we decided to utilize the knowledge avail- on Lexical-semantic and Ontological Resources, 2007. able in RDF/OWL EuroWordNet [3]. 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