Kiril Simov

OntoMap: portal for upper-level ontologies

Currently the evaluation of the feasibility of general-purposeontologies and upper-level models is expensive mostly because oftechnical problems such as different representation formalisms andterminologies used. Additionally, there are no formal mappingsbetween the upper-level ontologies that could ease any kind ofstudies and comparisons. We present the OntoMap Project(http://www.OntoMap.org), a project with the pragmatic goal tofacilitate the access, understanding, and reuse of such resources.A semantic framework on the conceptual level is implemented that issmall and easy enough to be learned on-the-fly. We tried to designthe framework so that it captures most of the semantics usuallyencoded in upper-level models. Technically, OntoMap is a web-siteproviding access to several upper-level ontologies and manualmapping between them.

Language technology for elearning

Given the huge amount of static and dynamic content created for eLearning tasks, the major challenge for extending their use is to improve the effectiveness of retrieval and accessibility by making use of Learning Management Systems. The aim of the European project Language Technology for eLearning is to tackle this problem by providing Language Technology based functionalities and by integrating semantic knowledge to facilitate the management, distribution and retrieval of the learning material.

Linking legal open data: breaking the accessibility and language barrier in european legislation and case law

In this paper we describe how the EUCases FP7 project is addressing the problem of lifting Legal Open Data to Linked Open Data to develop new applications for the legal information provision market by enriching structurally the documents (first of all with navigable references among legal texts) and semantically (with concepts from ontologies and classification). First we describe the social and economic need for breaking the accessibility barrier in legal information in the EU, then we describe the technological challenges and finally we explain how the EUCases project is addressing them by a combination of Human Language Technologies.

Cascaded regular grammars over XML documents

The basic mechanism of CLaRK for linguistic processing of text corpora is the cascade regular grammar processor. The main challenge to the grammars in question is how to apply them on XML encoding of the linguistic information. The system offers a solution using an XPath language for constructing the input word to the grammar and an XML encoding of the categories of the recognized words.

Improving the search for learning objects with keywords and ontologies

We report on an ongoing project which aims at improving the effectiveness of retrieval and accessibility of learning object within learning management systems and learning object repositories. The project Language Technology for eLearning approaches this task by providing Language Technology based functionalities and by integrating semantic knowledge through domain-specific ontologies. We will report about the development of a keyword extractor and a domain-specific ontology, the integration of these modules into the learning management system ILIAS and the validation of these tools which assesses their added value in the scenario of searching learning objects across different languages.

The Complexity of Modellability in Finite and ComputableSignatures of a Constraint Logic for Head-Driven PhraseStructure Grammar

AbstractThe SRL (speciate re-entrant logic) of King (1989) is a sound, complete and decidable logic designed specifically to support formalisms for the HPSG (head-driven phrase structure grammar) of Pollard and Sag (1994). The SRL notion of modellability in a signature is particularly important for HPSG, and the present paper modifies an elegant method due to Blackburn and Spaan (1993) in order to prove that modellability in each computable signature is Π10modellability in some finite signature is Π10-hard (hence not decidable), andmodellability in some finite signature is decidable. Since each finite signature is a computable signature, we conclude that Π01-completeness is the least upper bound on the complexity of modellability both in finite signatures and in computable signatures, though not a lower bound in either.

Crosslingual Retrieval in an eLearning Environment

In this paper we are reporting about an ongoing project LT4eL (Language Technolohy for eLearning) aiming at improving the effectiveness of retrieval and accessibility of learning objects within a learning management system. We elaborate the process of building the domain ontology and present the multilingual support offered to the application.

On the Performance of Query Rewriting in Vertically Distributed Cloud Databases

Cloud Computing with its dynamic pay as you go model and scalability characteristics promises computing on demand with associated cost savings compared to traditional computing architectures. This is a promising computing model especially in the context of Big Data. However, renting computing capabilities from a cloud provider means the integration of external resources into the own infrastructure and this requires a great amount of trust and raises new data security and privacy challenges. With respect to these still unsolved problems, this work presents a fixed vertical partitioning and distribution approach that uses traditional relational data models and distributes the corresponding partitions vertically across different cloud providers. So, every cloud provider only gets a small, but defined (and therefore fixed) logically independent chunk of the entire data, which is useless without the other parts. However, the distribution and the subsequent join of the data suffer from great performance losses, which are unbearable in practical usage scenarios. The novelty of our approach combines the well-known vertical database partitioning technique with a distribution logic that stores the vertical partitions at different cloud computing environments. Traditionally, vertical as well as horizontal partitioning approaches are used to improve the access to database data, but these approaches use dynamic and automated partitioning algorithms and schemes based on query workloads, data volumes, network bandwidth, etc. In contrast to this, our approach uses a fixed user-defined vertical partitioning approach, where no two critical attributes of a relation should be stored in a single partition. Thus, our approach aims at improving data security and privacy especially in public Cloud Computing environments, but raises the challenging research question of how to improve the data access to such fixed user-partitioned and distributed database environments. In this paper, we outline a query rewriting approach that parallelizes queries and joins in order to improve the query performance. We implemented our fixed partitioning and distribution approach based on the TPC-W benchmark and we finally present the performance results in this work.

The Automatic Deduction of Classificatory Systems from Linguistic Theories (Abridged)

Classifying linguistic objects is a widespread and important linguistic task, and computational linguistics often requires the deduction of a classificatory system from a general linguistic theory. Since hand deducing a classificatory system may consume much effort and introduce errors, a device that effectively deduces accurate classificatory systems from general linguistic theories would benefit computational linguistics. We present a prototypical abstract device that automatically deduces classificatory systems from finite linguistic theories.

A Multilingual Access Module to Legal Texts

The paper introduces a Multilingual Access Module. This module translates the user’s legislation query from its source language into the target language, and retrieves the detected texts that match the query. The service is demonstrated in its potential for two languages – English and Bulgarian, in both directions (English-to-Bulgarian and Bulgarian-to-English). The module consists of two submodules: Ontology-based and Statistical Machine Translation. Since both proposed submodules have some drawbacks, they are used in an integrated architecture, thus profiting from each other.