Jacek Małyszko

A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain

The paper presents a proposal for a framework for the identification, assessment and selection of open data sources based on certain quality criteria, such as accessibility, relevance, accuracy & reliability, clarity, timeliness & punctuality, and coherence & comparability. The framework concerns mainly open data sources and focuses on their quality. The open data are used to enhance existing internal data and to fuse them with data from other sources. The framework consists of few steps starting from definition of quality criteria based on review of relevant literature and user requirements, then identification of potential sources, sources assessment and selection, and finally data retrieval process. For each step, a specific approach is described, how it may be conducted in practice. The proposed framework is evaluated using a real use case scenario from the maritime domain. The main approach utilized in this use-case is the Delphi method with some characteristics of Analytic Hierarchy Process.

Named Entity Disambiguation for Maritime-related Data Retrieved from Heterogenous Sources

The article concerns integration and disambiguation of data related to the maritime domain. A developed system is described, which collects and merges data about several maritime‐related entities (vessels, vessel types, ports, companies etc.) retrieved from different internet sources and feeds the data into a single database. This process is however not trivial. There are few challenges, which need to be faced to successfully conduct it. Firstly, in different sources, entities may be referenced to in different ways, for example, by using different text strings. Additionally, some of these references may be ambiguous, i.e. potentially the reference may point to more than one entity. To enable efficient analysis of data coming from different sources, such ambiguities must be resolved automatically as a preprocessing step, before the data is uploaded to the database and utilized in further computations. The aim of the disambiguation process is to assign artificial, unique identifiers to each entity and then, if possible, automatically assign these identifiers to each data item related to a given entity. In the article, developed methods for resolving such ambiguities are discussed and their evaluation is presented. http://www.transnav.eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 10

Discovering of Users’ Interests Evolution Patterns for Learning Goals Recommendation

Building and utilizing users’ models to the end of better customized education products, especially in e-learning, is beneficial for both users and companies they work for. However, there is no general solution enhancing users’ choices concerning their long–term learning goals. In this paper, we introduce a method, that trough analysis of time–variable user models provides a structured collection of information on common patterns of users’ interests changes. Based on that, predictions can be made to reveal possible future changes in the fields of users’ interests. We argue, that such predictions can be helpful in learning goals recommendation.

A Methodology for Quality-Based Selection of Internet Data Sources in Maritime Domain

The paper presents a methodology for identification, assessment and selection of internet data sources that shall be used to supplement existing internal data in a continuous manner. Several criteria are specified to help in the selection process. The proposed method is described based on an example of the system for the maritime surveillance purposes, originally developed within the SIMMO research project. As a result, we also present a ranking of concrete data sources. The presented methodology is universal and can be applied to other domains, where internet sources can offer additional data.

Architecture of Maritime Awareness System Supplied with External Information

Abstract In this paper, we discuss a software architecture, which has been developed for the needs of the System for Intelligent Maritime Monitoring (SIMMO). The system bases on the state-of-the-art information fusion and intelligence analysis techniques, which generates an enhanced Recognized Maritime Picture and thus supports situation analysis and decision- making. The SIMMO system aims to automatically fuse an up-to-date maritime data from Automatic Identification System (AIS) and open Internet sources. Based on collected data, data analysis is performed to detect suspicious vessels. Functionality of the system is realized in a number of different modules (web crawlers, data fusion, anomaly detection, visualization modules) that share the AIS and external data stored in the system’s database. The aim of this article is to demonstrate how external information can be leveraged in maritime awareness system and what software solutions are necessary. A working system is presented as a proof of concept.

Aspect-Aware Identification of Opinion Phrases Polarity Based on Summaries of Consumer Opinions about Products and Services

In this paper, we propose a novel approach to identification of opinion words polarity (so-called polarity induction) for opinion words lexicon extraction. The method employs summaries of many reviews of a single product (or service) as a prediction of polarity of opinion words describing different aspects of the said product. In the article a preliminary experimentation is presented on the basis of which we can expect that the proposed approach can be used in polarity identification.