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Ceglarek D.,Poznan School of Banking | Haniewicz K.,Poznań University of Economics | Rutkowski W.,CIBER ISCIII
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

This work presents results of the ongoing novel research in the area of semantic networks, plagiarism detection and general natural language processing. Results presented here demonstrate that the semantic compression is a valuable addition to the existing methods used in plagiary detection. The application of the semantic compression boosts the efficiency of Sentence Hashing Algorithm for Plagiarism Detection (SHAPD) and authors' implementation of the w-shingling algorithm. There were also test with use of the traditional Vector Space Model method that demonstrated that this technique is not well suited for plagiary detection contrary to general beliefs. All the experiments were performed on a generally available corpus built so that such analysis can be comparable to efforts of other research teams. © 2012 Springer-Verlag.


Ceglarek D.,Poznan School of Banking
2013 The International Conference on Technological Advances in Electrical, Electronics and Computer Engineering, TAEECE 2013 | Year: 2013

This work presents results of the ongoing research in the area of natural language processing focusing on plagiarism detection, applying semantic networks and semantic compression. The results demonstrate that the semantic compression is a valuable addition to the existing methods used in plagiary detection. The application of the semantic compression boosts the efficiency of Sentence Hashing Algorithm for Plagiarism Detection 2 (SHAPD2) and w - shingling algorithm. Experiments were performed on Clough & Stephenson corpus as well as on an available PAN-PC plagiarism corpus used to evaluate plagiarism detection methods, so the results can be compared with other research teams. © 2013 IEEE.


Ceglarek D.,Poznan School of Banking
Studies in Computational Intelligence | Year: 2014

This paper describes a new algorithm identifying common phrase sequences. The SHAPD2 algorithm was designed to achieve the goal of a single-pass corpus to corpus comparison. It is a highly efficient solution that finds application with considerable amount of data and excels over other approaches. One of its possible applications is the detection of potential plagiarisms by comparing not a document against a corpus, but corpus to corpus. This makes the SHAPD2 algorithm a valuable alternative to the available solutions. © Springer International Publishing Switzerland 2014.


Ceglarek D.,Poznan School of Banking
Advances in Intelligent Systems and Computing | Year: 2013

This paper presents the structure and the functionality of the Semantically Enhanced Intellectual Property Protection System. The system uses an extensive set of semantic net algorithms for the Polish and English language that which allows it to detect similarities between compared documents on a level far beyond simple text matching. SEIPro2S benefits result both from using a local document repository and from Web based resources. The SeiPro2S system uses a mechanism of semantic compression developed to generalize concepts during a comparison of documents. The main focus of this work is to give the reader an overview of architecture, applied mechanisms and some actual results. © Springer International Publishing Switzerland 2013.


Ceglarek D.,Poznan School of Banking | Haniewicz K.,Poznań University of Economics
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

This work presents a Sentence Hashing Algorithm for Plagiarism Detection - SHAPD. To present a user with the best results the algorithm makes use of special trait of the written texts - their natural sentence fragmentation, later employing a set of special techniques for text representation. Results obtained demonstrate that the algorithm delivers solution faster than the alternatives. Its algorithmic complexity is logarithmic, thus its performance is better than most algorithms using dynamic programming used to find the longest common subsequence. © 2012 Springer-Verlag Berlin Heidelberg.


Ceglarek D.,Poznan School of Banking
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

Ongoing research on novel methods and tools that can be applied in Natural Language Processing tasks has resulted in the design of a semantic compression mechanism. Semantic compression is a technique that allows for correct generalization of terms in some given context. Thanks to this generalization a common thought can be detected. The rules governing the generalization process are based on a data structure which is referred to as a domain frequency dictionary. Having established the domain for a given text fragment the disambiguation of possibly many hypernyms becomes a feasible task. Semantic compression, thus an informed generalization, is possible through the use of semantic networks as a knowledge representation structure. In the given overview, it is worth noting that the semantic compression allows for a number of improvements in comparison to already established Natural Language Processing techniques. These improvements, along with a detailed discussion of the various elements of algorithms and data structures that are necessary to make semantic compression a viable solution, are the core of this work. Semantic compression can be applied in a variety of scenarios, e.g. in detection of plagiarism. With increasing effort being spent on developing semantic compression, new domains of application have been discovered. What is more, semantic compression itself has evolved and has been refined by the introduction of new solutions that boost the level of disambiguation efficiency. Thanks to the remodeling of already existing data sources to suit algorithms enabling semantic compression, it has become possible to use semantic compression as a base for automata that, thanks to the exploration of hypernym-hyponym and synonym relations, new concepts that may be included in the knowledge representation structures can now be discovered. © Springer-Verlag Berlin Heidelberg 2014


Ceglarek D.,Poznan School of Banking | Haniewicz K.,Poznań University of Economics | Rutkowski W.,Business Center Poland
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

Article presents results of implementation of semantic compression for English. An idea of semantic compression is reintroduced with examples and steps taken to perform experiment are given. A task of re-engineering available structures in order to apply them to already existing project infrastructure for experiments is described. Experiment demonstrates validity of research along with real examples of semantically compressed documents. © 2010 Springer-Verlag Berlin Heidelberg.


Ceglarek D.,Poznan School of Banking | Haniewicz K.,Poznań University of Economics | Rutkowski W.,Business Center Poland
Studies in Computational Intelligence | Year: 2010

The aim of this work is to present methods some of the ongoing research done as a part of development of Semantically Enhanced Intellectual Property Protection System - SEIPro2S. Main focus is on description of methods that allow for creation of more concise documents preserving semantically the same meaning as their originals. Thus, compacting methods are denoted as a semantic compression. © 2010 Springer-Verlag Berlin Heidelberg.


Ceglarek D.A.,Poznan School of Banking
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

This paper presents the issues concerning knowledge protection and, in particular, research in the area of natural language processing focusing on plagiarism detection, semantic networks and semantic compression. The results demonstrate that the semantic compression is a valuable addition to the existing methods used in plagiarism detection. The application of the semantic compression boosts the efficiency of the Sentence Hashing Algorithm for Plagiarism Detection 2 (SHAPD2) and the w-shingling algorithm. All experiments were performed on an available PAN-PC plagiarism corpus used to evaluate plagiarism detection methods, so the results can be compared with other research teams. © 2013 Springer-Verlag.


Nowinski W.,Poznan School of Banking | Rialp A.,Autonomous University of Barcelona
Journal for East European Management Studies | Year: 2013

This paper contributes to SME internationalization theory by offering regionspecific propositions on early internationalization of Central and Eastern European (CEE) firms. We suggest that special treatment of international new ventures from CEE transition economies is justified due to constraints faced by their founders, particularly not only limited financial resources but also relatively low human and social capital. We propose that some of the regionspecific drivers which contribute to early internationalization involve domestic market entry barriers and arbitrage opportunities related to the higher purchasing power of consumers from developed economies. Additionally, we find that in order to overcome resource limitations, CEE international new ventures apply effectuation and bricolage to exploit controlled resources and flexibly adapt to the market situation.

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