Papers by Ioannis Kopanakis
In this paper we describe an application of our approach to temporal text mining in Competitive I... more In this paper we describe an application of our approach to temporal text mining in Competitive Intelligence for the biotechnology and pharmaceutical industry. The main objective is to identify changes and trends of associations among entities of interest that appear in text over time. Text Mining (TM) exploits information contained in textual data in various ways, including the type of analyses that are typically performed in Data Mining [17]. Information Extraction (IE) facilitates the semi-automatic creation of metadata repositories from text. Temporal Text mining combines Information Extraction and Data Mining techniques upon textual repositories and incorporates time and ontologies" issues. It consists of three main phases; the Information Extraction phase, the ontology driven generalisation of templates and the discovery of associations over time. Treatment of the temporal dimension is essential to our approach since it influences both the annotation part (IE) of the syst...
Clustering approaches organize a set of objects into groups whose members are proximate according... more Clustering approaches organize a set of objects into groups whose members are proximate according to some similarity function defined on lowlevel features, assuming that their values are not subject to any kind of uncertainty. Furthermore, these methods assume that similarity is measured by accounting only the degree in which two entities are related, ignoring the hesitancy introduced by the degree in which they are unrelated. Challenged by real-world clustering problems this paper proposes a novel fuzzy clustering scheme of datasets produced in the context of intuitionistic fuzzy set theory. More specifically, we introduce a variant of the Fuzzy C-Means (FCM) clustering algorithm that copes with uncertainty and a similarity measure between intuitionistic fuzzy sets, which is appropriately integrated in the clustering algorithm. To evaluate our approach, we describe an intuitionistic fuzzification of color digital images upon which we applied the proposed scheme. The experimental ev...
The visual senses for humans have a unique status, offering a very broadband channel for informat... more The visual senses for humans have a unique status, offering a very broadband channel for information flow. Visual approaches to analysis and mining attempt to take advantage of our abilities to perceive pattern and structure in visual form and to make sense of, or interpret, what we see. Visual Data Mining techniques have proven to be of high value in
International Journal of Business Intelligence and Data Mining, 2011
In this paper we describe our approach to discover trends for the biotechnology and pharmaceutica... more In this paper we describe our approach to discover trends for the biotechnology and pharmaceutical industry based on temporal text mining. Temporal text mining combines information extraction and data mining techniques upon textual repositories and our main objective is to identify changes of associations among entities of interest over time. It consists of three Discovering market trends in the biotechnology industry 185 main phases; the Information Extraction, the ontology driven generalisation of templates and the discovery of associations over time. Treatment of the temporal dimension is essential to our approach since it influences both the annotation part (IE) of the system as well as the mining part.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009
We propose a method for trajectory classification based on trajectory voting in Moving Object Dat... more We propose a method for trajectory classification based on trajectory voting in Moving Object Databases (MOD). Trajectory voting is performed based on local trajectory similarity. This is a relatively new topic in the spatial and spatiotemporal database literature with a variety of applications like trajectory summarization, classification, searching and retrieval. In this work, we have used moving object databases in space, acquiring spatiotemporal 3-D trajectories, consisting of the 2-D geographic location and the 1-D time information. Each trajectory is modelled by sequential 3-D line segments. The global voting method is applied for each segment of the trajectory, forming a local trajectory descriptor. By the analysis of this descriptor the representative paths of the trajectory can be detected, that can be used to visualize a MOD. Our experimental results verify that the proposed method efficiently classifies trajectories and their sub-trajectories based on a robust voting method.
Conventional Content-Based Image Retrieval (CBIR) systems make use of similarity measures estimat... more Conventional Content-Based Image Retrieval (CBIR) systems make use of similarity measures estimated directly from low-level image features, involving multidimensional and exhaustive, nearest neighbor searching. In this paper we present an image retrieval methodology suited for efficient search in cultural heritage images that utilizes similarity measures defined over higher-level patterns associated with clusters of low-level image features. The similarity between two patterns is estimated as a function of the similarity between both the structure and the measure components of the patterns. We evaluate our system using cultural heritage images derived from the repository of the Foundation of Hellenic World (FHW). For the experiments we use Local Binary Pattern (LBP) and contrast distributions as image features and the results show that the proposed pattern-based approach efficiently retrieves images compared to commonly employed methods.
The main objective of the present work was to study the variation of particulate PAHs (EPA priori... more The main objective of the present work was to study the variation of particulate PAHs (EPA priority components) in the urban area of the coastal city Chania (Western Crete, Greece), as well as in its suburban area (Kounoupidiana, Akrotiri) and to estimate the health risks, according to the toxicity equivalency factors (TEFs) (Nisbet & LaGoy, 1992). Duplicates of samples of
IEEE International Conference on Data Mining, 2009
Knowledge discovery in Trajectory Databases (TD) is an emerging field which has recently gained g... more Knowledge discovery in Trajectory Databases (TD) is an emerging field which has recently gained great interest; on the other hand the inherent presence of uncertainty in TD during the mining process has not been taken yet into account. Current approaches group trajectories together by accounting only the degree of their similarity, ignoring at the same time the degree in which
In recent years numerous research efforts were focused in the examination of the relationship bet... more In recent years numerous research efforts were focused in the examination of the relationship between the exposure of humans to the particulate matter (PM) and consecutive adverse health effects (Schwartz, 1994). The quality of air in the indoor environment has become of great importance as people nowadays spend about 80% of their time indoors. Moreover a large portion of their
... stored in both local and public medical databases is growing, efficient image indexing and re... more ... stored in both local and public medical databases is growing, efficient image indexing and retrieval ... clustering algorithm is used to cluster the pixels and to find regions in ... Belongie, Greenspan and Malik, 2002; Chen, Wang, Krovetz, 2005) with a semantically rich representation ...
In this paper we present an overview of the MetaOn system. The core target of MetaOn is to constr... more In this paper we present an overview of the MetaOn system. The core target of MetaOn is to construct and integrate semantically rich metadata extracted from documents, images and linguistic resources, to facilitate intelligent search and analysis. The MetaOn framework involves ontology-based information extraction and data mining, sem i- automatic construction of domain specific ontologies, content-based image indexing and retrieval,
We study the problem of classification as this is presented in the context of data mining. Among ... more We study the problem of classification as this is presented in the context of data mining. Among the various approaches that are investigated, we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classification of numerical data, followed by the
Intl. Workshop on Pattern Representation and Management, 2004
The purpose of this paper is to study the problem of pattern classification as this is presented ... more The purpose of this paper is to study the problem of pattern classification as this is presented in the context of data mining. Among the various approaches we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classification of numerical
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Papers by Ioannis Kopanakis