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Developing hardware, algorithms and protocols, as well as collecting data in sensor networks are all important challenges in building good systems. We describe a vertical system integration of a sensor node and a toolkit of machine learning algorithms. Based on a dataset that combines sensor data with additional introduced data we predict the number of persons in a closed space. We analyze the dataset...
In this paper, we present a document visualization technique for data analysis based on the semantic representation of text in the form of a directed graph, referred to as semantic graph. It is derived using natural language processing as follows. Firstly subject- verb-object triplets are automatically extracted from the Penn Treebank parse tree obtained for each sentence in the document. Secondly,...
This paper presents experiments with applying social network analysis on data about editing of semantic media wiki. As a number of users are editing the same wiki pages, one can view them as a social network of people interacting via wiki pages. We propose representation of the wiki editing log files as a graph either of users that are connected if they are editing the same pages or of pages that...
Capturing information about employees can give organizations insight into underlying knowledge processes. Analyzing email communications, for example, can produce an informal structure that's flexible and that organizations can recalculate regularly to capture information flow among employees. The structure could also help institutions to both identify collaboration patterns and predict changes in...
Given publication titles and authors, what can we say about the evolution of scientific topics and communities over time? Which communities shrunk, which emerged, and which split, over time? And, when in time were the turning points? We propose TimeFall, which can automatically answer these questions given a social network/graph that evolves over time. The main novelty of the proposed approach is...
This paper presents several aspects of evaluating semi-automatic ontology generation techniques in real-world setting. We provide description of incorporating the techniques in a solution to real-world problem as performed by the end-users and evaluation of the techniques in several real-world scenarios. In addition we give a summary of user-study evaluation of semiautomatic data-driven tool for the...
We present design and results of a user study undertaken in order to evaluate ontology generation process. We have applied our study to an example tool for semi-automatic ontology generation OntoGen that covers different stages of the underlying process. In-depth analysis of the user experience delivered valuable insights into the requirements for the further system development.
This paper presents an approach for constructing an ontology from a stream of documents. Named entities extracted from the documents are used as instances of the ontology. Entities and co-occurring entity pairs are represented by feature vectors based on the content of the documents where they occurred. In general, concepts and relations can be formed into an ontological structure either by clustering...
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