Comprehensive Review of Opinion Summarization

The abundance of opinions on the web has kindled the study of opinion summarization over the last few years. People have introduced various techniques and paradigms to solving this special task. This survey attempts to systematically investigate the different techniques and approaches used in opinion summarization. We provide a multi-perspective classification of the approaches used and highlight some of the key weaknesses of these approaches. This survey also covers evaluation techniques and data sets used in studying the opinion summarization problem. Finally, we provide insights into some of the challenges that are left to be addressed as this will help set the trend for future research in this area.unpublishednot peer reviewe

Semantic enrichment of knowledge sources supported by domain ontologies

This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.European research projects - CoSpaces (IST-5-034245), CRESCENDO (FP7-234344) and MobiS (FP7-318452

Geospatial crowdsourced data fitness analysis for spatial data infrastructure based disaster management actions

The reporting of disasters has changed from official media reports to citizen reporters who are at the disaster scene. This kind of crowd based reporting, related to disasters or any other events, is often identified as 'Crowdsourced Data' (CSD). CSD are freely and widely available thanks to the current technological advancements. The quality of CSD is often problematic as it is often created by the citizens of varying skills and backgrounds. CSD is considered unstructured in general, and its quality remains poorly defined. Moreover, the CSD's location availability and the quality of any available locations may be incomplete. The traditional data quality assessment methods and parameters are also often incompatible with the unstructured nature of CSD due to its undocumented nature and missing metadata. Although other research has identified credibility and relevance as possible CSD quality assessment indicators, the available assessment methods for these indicators are still immature. In the 2011 Australian floods, the citizens and disaster management administrators used the Ushahidi Crowd-mapping platform and the Twitter social media platform to extensively communicate flood related information including hazards, evacuations, help services, road closures and property damage. This research designed a CSD quality assessment framework and tested the quality of the 2011 Australian floods' Ushahidi Crowdmap and Twitter data. In particular, it explored a number of aspects namely, location availability and location quality assessment, semantic extraction of hidden location toponyms and the analysis of the credibility and relevance of reports. This research was conducted based on a Design Science (DS) research method which is often utilised in Information Science (IS) based research. Location availability of the Ushahidi Crowdmap and the Twitter data assessed the quality of available locations by comparing three different datasets i.e. Google Maps, OpenStreetMap (OSM) and Queensland Department of Natural Resources and Mines' (QDNRM) road data. Missing locations were semantically extracted using Natural Language Processing (NLP) and gazetteer lookup techniques. The Credibility of Ushahidi Crowdmap dataset was assessed using a naive Bayesian Network (BN) model commonly utilised in spam email detection. CSD relevance was assessed by adapting Geographic Information Retrieval (GIR) relevance assessment techniques which are also utilised in the IT sector. Thematic and geographic relevance were assessed using Term Frequency – Inverse Document Frequency Vector Space Model (TF-IDF VSM) and NLP based on semantic gazetteers. Results of the CSD location comparison showed that the combined use of non-authoritative and authoritative data improved location determination. The semantic location analysis results indicated some improvements of the location availability of the tweets and Crowdmap data; however, the quality of new locations was still uncertain. The results of the credibility analysis revealed that the spam email detection approaches are feasible for CSD credibility detection. However, it was critical to train the model in a controlled environment using structured training including modified training samples. The use of GIR techniques for CSD relevance analysis provided promising results. A separate relevance ranked list of the same CSD data was prepared through manual analysis. The results revealed that the two lists generally agreed which indicated the system's potential to analyse relevance in a similar way to humans. This research showed that the CSD fitness analysis can potentially improve the accuracy, reliability and currency of CSD and may be utilised to fill information gaps available in authoritative sources. The integrated and autonomous CSD qualification framework presented provides a guide for flood disaster first responders and could be adapted to support other forms of emergencies

Methodological approaches and techniques for designing ontologies in information systems requirements engineering

Programa doutoral em Information Systems and TechnologyThe way we interact with the world around us is changing as new challenges arise, embracing innovative business models, rethinking the organization and processes to maximize results, and evolving change management. Currently, and considering the projects executed, the methodologies used do not fully respond to the companies' needs. On the one hand, organizations are not familiar with the languages used in Information Systems, and on the other hand, they are often unable to validate requirements or business models. These are some of the difficulties encountered that lead us to think about formulating a new approach. Thus, the state of the art presented in this paper includes a study of the models involved in the software development process, where traditional methods and the rivalry of agile methods are present. In addition, a survey is made about Ontologies and what methods exist to conceive, transform, and represent them. Thus, after analyzing some of the various possibilities currently available, we began the process of evolving a method and developing an approach that would allow us to design ontologies. The method we evolved and adapted will allow us to derive terminologies from a specific domain, aggregating them in order to facilitate the construction of a catalog of terminologies. Next, the definition of an approach to designing ontologies will allow the construction of a domain-specific ontology. This approach allows in the first instance to integrate and store the data from different information systems of a given organization. In a second instance, the rules for mapping and building the ontology database are defined. Finally, a technological architecture is also proposed that will allow the mapping of an ontology through the construction of complex networks, allowing mapping and relating terminologies. This doctoral work encompasses numerous Research & Development (R&D) projects belonging to different domains such as Software Industry, Textile Industry, Robotic Industry and Smart Cities. Finally, a critical and descriptive analysis of the work done is performed, and we also point out perspectives for possible future work.A forma como interagimos com o mundo à nossa volta está a mudar à medida que novos desafios surgem, abraçando modelos empresariais inovadores, repensando a organização e os processos para maximizar os resultados, e evoluindo a gestão da mudança. Atualmente, e considerando os projetos executados, as metodologias utilizadas não respondem na totalidade às necessidades das empresas. Por um lado, as organizações não estão familiarizadas com as linguagens utilizadas nos Sistemas de Informação, por outro lado, são muitas vezes incapazes de validar requisitos ou modelos de negócio. Estas são algumas das dificuldades encontradas que nos levam a pensar na formulação de uma nova abordagem. Assim, o estado da arte apresentado neste documento inclui um estudo dos modelos envolvidos no processo de desenvolvimento de software, onde os métodos tradicionais e a rivalidade de métodos ágeis estão presentes. Além disso, é efetuado um levantamento sobre Ontologias e quais os métodos existentes para as conceber, transformar e representar. Assim, e após analisarmos algumas das várias possibilidades atualmente disponíveis, iniciou-se o processo de evolução de um método e desenvolvimento de uma abordagem que nos permitisse conceber ontologias. O método que evoluímos e adaptamos permitirá derivar terminologias de um domínio específico, agregando-as de forma a facilitar a construção de um catálogo de terminologias. Em seguida, a definição de uma abordagem para conceber ontologias permitirá a construção de uma ontologia de um domínio específico. Esta abordagem permite em primeira instância, integrar e armazenar os dados de diferentes sistemas de informação de uma determinada organização. Num segundo momento, são definidas as regras para o mapeamento e construção da base de dados ontológica. Finalmente, é também proposta uma arquitetura tecnológica que permitirá efetuar o mapeamento de uma ontologia através da construção de redes complexas, permitindo mapear e relacionar terminologias. Este trabalho de doutoramento engloba inúmeros projetos de Investigação & Desenvolvimento (I&D) pertencentes a diferentes domínios como por exemplo Indústria de Software, Indústria Têxtil, Indústria Robótica e Smart Cities. Finalmente, é realizada uma análise critica e descritiva do trabalho realizado, sendo que apontamos ainda perspetivas de possíveis trabalhos futuros

Semantic multimedia modelling & interpretation for search & retrieval

With the axiomatic revolutionary in the multimedia equip devices, culminated in the proverbial proliferation of the image and video data. Owing to this omnipresence and progression, these data become the part of our daily life. This devastating data production rate accompanies with a predicament of surpassing our potentials for acquiring this data. Perhaps one of the utmost prevailing problems of this digital era is an information plethora. Until now, progressions in image and video retrieval research reached restrained success owed to its interpretation of an image and video in terms of primitive features. Humans generally access multimedia assets in terms of semantic concepts. The retrieval of digital images and videos is impeded by the semantic gap. The semantic gap is the discrepancy between a user’s high-level interpretation of an image and the information that can be extracted from an image’s physical properties. Content- based image and video retrieval systems are explicitly assailable to the semantic gap due to their dependence on low-level visual features for describing image and content. The semantic gap can be narrowed by including high-level features. High-level descriptions of images and videos are more proficient of apprehending the semantic meaning of image and video content. It is generally understood that the problem of image and video retrieval is still far from being solved. This thesis proposes an approach for intelligent multimedia semantic extraction for search and retrieval. This thesis intends to bridge the gap between the visual features and semantics. This thesis proposes a Semantic query Interpreter for the images and the videos. The proposed Semantic Query Interpreter will select the pertinent terms from the user query and analyse it lexically and semantically. The proposed SQI reduces the semantic as well as the vocabulary gap between the users and the machine. This thesis also explored a novel ranking strategy for image search and retrieval. SemRank is the novel system that will incorporate the Semantic Intensity (SI) in exploring the semantic relevancy between the user query and the available data. The novel Semantic Intensity captures the concept dominancy factor of an image. As we are aware of the fact that the image is the combination of various concepts and among the list of concepts some of them are more dominant then the other. The SemRank will rank the retrieved images on the basis of Semantic Intensity. The investigations are made on the LabelMe image and LabelMe video dataset. Experiments show that the proposed approach is successful in bridging the semantic gap. The experiments reveal that our proposed system outperforms the traditional image retrieval systems

Integrative Levels of Knowing

Diese Dissertation beschäftigt sich mit einer systematischen Organisation der epistemologischen Dimension des menschlichen Wissens in Bezug auf Perspektiven und Methoden. Insbesondere wird untersucht inwieweit das bekannte Organisationsprinzip der integrativen Ebenen, das eine Hierarchie zunehmender Komplexität und Integration beschreibt, geeignet ist für eine grundlegende Klassifikation von Perspektiven bzw. epistemischen Bezugsrahmen. Die zentrale These dieser Dissertation geht davon aus, dass eine angemessene Analyse solcher epistemischen Kontexte in der Lage sein sollte, unterschiedliche oder gar konfligierende Bezugsrahmen anhand von kontextübergreifenden Standards und Kriterien vergleichen und bewerten zu können. Diese Aufgabe erfordert theoretische und methodologische Grundlagen, welche die Beschränkungen eines radikalen Kontextualismus vermeiden, insbesondere die ihm innewohnende Gefahr einer Fragmentierung des Wissens aufgrund der angeblichen Inkommensurabilität epistemischer Kontexte. Basierend auf Jürgen Habermas‘ Theorie des kommunikativen Handelns und seiner Methodologie des hermeneutischen Rekonstruktionismus, wird argumentiert, dass epistemischer Pluralismus nicht zwangsläufig zu epistemischem Relativismus führen muss und dass eine systematische Organisation der Perspektivenvielfalt von bereits existierenden Modellen zur kognitiven Entwicklung profitieren kann, wie sie etwa in der Psychologie oder den Sozial- und Kulturwissenschaften rekonstruiert werden. Der vorgestellte Ansatz versteht sich als ein Beitrag zur multi-perspektivischen Wissensorganisation, der sowohl neue analytische Werkzeuge für kulturvergleichende Betrachtungen von Wissensorganisationssystemen bereitstellt als auch neue Organisationsprinzipien vorstellt für eine Kontexterschließung, die dazu beitragen kann die Ausdrucksstärke bereits vorhandener Dokumentationssprachen zu erhöhen. Zudem enthält der Anhang eine umfangreiche Zusammenstellung von Modellen integrativer Wissensebenen.This dissertation is concerned with a systematic organization of the epistemological dimension of human knowledge in terms of viewpoints and methods. In particular, it will be explored to what extent the well-known organizing principle of integrative levels that presents a developmental hierarchy of complexity and integration can be applied for a basic classification of viewpoints or epistemic outlooks. The central thesis pursued in this investigation is that an adequate analysis of such epistemic contexts requires tools that allow to compare and evaluate divergent or even conflicting frames of reference according to context-transcending standards and criteria. This task demands a theoretical and methodological foundation that avoids the limitation of radical contextualism and its inherent threat of a fragmentation of knowledge due to the alleged incommensurability of the underlying frames of reference. Based on Jürgen Habermas’s Theory of Communicative Action and his methodology of hermeneutic reconstructionism, it will be argued that epistemic pluralism does not necessarily imply epistemic relativism and that a systematic organization of the multiplicity of perspectives can benefit from already existing models of cognitive development as reconstructed in research fields like psychology, social sciences, and humanities. The proposed cognitive-developmental approach to knowledge organization aims to contribute to a multi-perspective knowledge organization by offering both analytical tools for cross-cultural comparisons of knowledge organization systems (e.g., Seven Epitomes and Dewey Decimal Classification) and organizing principles for context representation that help to improve the expressiveness of existing documentary languages (e.g., Integrative Levels Classification). Additionally, the appendix includes an extensive compilation of conceptions and models of Integrative Levels of Knowing from a broad multidisciplinary field

The Social Sustainability of Digital Information Services in Sub-Saharan Africa

Nowadays, mobile phone-enabled services are reaching the rural poor farmer in Sub-Saharan Africa (SSA) with digital information for agricultural development. These digital services consist of access to social networks and customised information that are expected to enhance farm management due to knowledge exchange and learning. This thesis aimed to analyse the farmers’ use of digital services and discuss its implications for social sustainability in agriculture by looking at how digital information merges, coexists or competes with other bodies of local knowledge. The analysis was based on participant observation with eleven farmers that use iShamba, a digital platform providing agricultural information services to smallholder farmers in rural Kenya. A social practice perspective implies that digital information must consider the contextual realities of farmers in terms of material, competence and meaning. Considering that access to inputs is constrained in the context of the study, this thesis suggests that digital services could contribute to social sustainability by promoting biological-based innovations that are locally applicable in terms of the materials available to farmers. Moreover, digital services could complement their service with field advisory visits or training courses, where the role of human intermediation appeared to be fundamental. Social sustainability in agriculture is that associated with the generation of knowledge and meaning that legitimises a particular model of agricultural development. This thesis found that digital services increase the diversity of knowledge by offering several options to farmers which contributes to social sustainability in agriculture. However, digital services do not encourage innovation, directing research toward attending to the demands of poor rural farmers but rather provide farmers with the available innovations. Additionally, a key point is the potential of digital services to co-construct the meaning associated with agricultural development. But since digital information integrates diverse trajectories of agricultural development, social sustainability requires that the institutional arrangement promote and support models of sustainable agriculture at the landscape leve

Representing archaeological uncertainty in cultural informatics

This thesis sets out to explore, describe, quantify, and visualise uncertainty in a cultural informatics context, with a focus on archaeological reconstructions. For quite some time, archaeologists and heritage experts have been criticising the often toorealistic appearance of three-dimensional reconstructions. They have been highlighting one of the unique features of archaeology: the information we have on our heritage will always be incomplete. This incompleteness should be reflected in digitised reconstructions of the past. This criticism is the driving force behind this thesis. The research examines archaeological theory and inferential process and provides insight into computer visualisation. It describes how these two areas, of archaeology and computer graphics, have formed a useful, but often tumultuous, relationship through the years. By examining the uncertainty background of disciplines such as GIS, medicine, and law, the thesis postulates that archaeological visualisation, in order to mature, must move towards archaeological knowledge visualisation. Three sequential areas are proposed through this thesis for the initial exploration of archaeological uncertainty: identification, quantification and modelling. The main contributions of the thesis lie in those three areas. Firstly, through the innovative design, distribution, and analysis of a questionnaire, the thesis identifies the importance of uncertainty in archaeological interpretation and discovers potential preferences among different evidence types. Secondly, the thesis uniquely analyses and evaluates, in relation to archaeological uncertainty, three different belief quantification models. The varying ways that these mathematical models work, are also evaluated through simulated experiments. Comparison of results indicates significant convergence between the models. Thirdly, a novel approach to archaeological uncertainty and evidence conflict visualisation is presented, influenced by information visualisation schemes. Lastly, suggestions for future semantic extensions to this research are presented through the design and development of new plugins to a search engine