ServiceDesigner: a tool to help end-users become individual service providers

Pervasive and ubiquitous computing will fundamentally change the mode of interaction between humans and computers;instead of working with applications on a desktop computer we will interact with our environment through electronic services-anytime and anywhere. In this new modus operandi, specialized and personalized services will become much more important; the usual software house solutions may not be sufficient for individual demands.We propose that end-users themselves can be the service providers; the incentive to create services is grounded in each individuals personal demand for well suited services and this demand will only increase when technology makes it possible to access services ubiquitously. Individual Service Provisioning requires three parts: a general platform for managing and accessing electronic services; simple but powerful tools to create the services; and the means to share services between users. Building on previous work developing sView, a personal service environment, this paper presents the second part - ServiceDesigner - a tool for creating new services for sView. ServiceDesigner, using webservices that expose the functions of web sites as programmatically accessible components, lets end-users create personalized and functional electronic services that fit in the personal platform. With ServiceDesigner, web services are directly available to users and finished services can also be shared with other users

Technical Requirements For Knowledge Representation For Attitude Mining On A Realistic Scale

To be useful, a reputation mining system must cover a broad range of weakly, vaguely, and implicitly expressed human sentiments andcannot in the absence of prior knowledge rely on sampling the data stream of human-generated text. To achieve coverage, a reputationmining system must be sensitive to variation and change in the signal. These requirements pose a challenge which are an instance ofmore general semantic processing – this paper presents some design requirements used to design and implement a semantic layer for aprocessing stack for human-generated information.QC 20130204</p

Usefulness of Sentiment Analysis

What can text sentiment analysis technology be used for,and does a more usage-informed view on sentiment analysis pose newrequirements on technology development?QC 20130204Part of proceedings ISBN 978-3-642-28997-2</p

Profiling Reputation of Corporate Entities in Semantic Space : Notebook for RepLab at CLEF 2012

Gavagai used its first-generation baseline system for the profiling taskfor evaluation campaign for online reputation management systems of CLEF2012. The system builds on large scale analysis of streaming text and performedexcellently on this task with standard settings.QC 20130204</p

Profiling Reputation of Corporate Entities in Semantic Space : Notebook for RepLab at CLEF 2012

Gavagai used its first-generation baseline system for the profiling taskfor evaluation campaign for online reputation management systems of CLEF2012. The system builds on large scale analysis of streaming text and performedexcellently on this task with standard settings.QC 20130204</p

O.: Usefulness of sentiment analysis

Abstract. What can text sentiment analysis technology be used for, and does a more usage-informed view on sentiment analysis pose new requirements on technology development? 1 Human emotion, attitude, mood, affect, sentiment, opinion, and appeal Analysis of sentiment in text is a new and rapidly growing field of study and application. This paper outlines some application areas for sentiment analysis technology, and discusses what requirements a technology for sentiment analysis of text should be able to answer to. The human sensations of emotion, attitude, mood, affect, sentiment, opinion, and appeal all contribute to the basic categories of sentiment analysis of text, but they have been studied in their own right for a long time. Traditionally, this has been done in the behavioural sciences; [9] but today also by information technologists, especially with respect to interaction design . &quot;Emotion&quot; , &quot;attitude&quot; , &quot;mood&quot; &quot;affect&quot;, &quot;sentiment&quot; , and &quot;appeal&quot; are everyday words. No consensus beyond the general vernacular usage of the most common terms can currently be assumed, but mostly the usage tends to hold that affect or affective state is the more general term, emotion a momentary, mostly conscious sensation, and mood an affective frame over a longer time span, not necessarily consciously acknowledged by its holder. These affective aspects of human behaviour and information processing are studied in various ways with variously differing perspectives, but the assumptions of most researchers is that people are in continuously changing affective states of some sort; and that activities people engage in have emotional impact and that their decision making, behaviour, and performance are informed by the affective state of the user. This appears to be true even for very mundane tasks such as workplace tasks or accessing information items, but most importantly for the purposes of this paper, in producing and understanding information items, and, it is assumed, even to the extent that mood, with respect to some topic or facet of life, will colour and influence the understanding, generation, or processing of information on another quite different topic. Sentiment analysis of text typically assumes that lexical items found in the text carry attitudinal loading. Previous work on the loading of individual features and the affective reaction of human subjects to linguistic items on the level of words and term

Analysis of Open Answers to Survey Questions throughInteractive Clustering and Theme Extraction

This paper describes design principles for and the implementation of Gavagai Explorer—a new application which builds on interactive text clustering to extract themes from topically coherent text sets such as open text answers to surveys or questionnaires.An automated system is quick, consistent, and has full coverage over the study material. A system allows an analyst to analyze more answers in a given time period; provides the same initial results regardless of who does the analysis, reducing the risks of inter-rater discrepancy; and does not risk miss responses due to fatigue or boredom. These factors reduce the cost and increase the reliability of the service. The most important feature, however, is relieving the human analyst from the frustrating aspects of the coding task, freeing the effort to the central challenge of understanding themes. Gavagai Explorer is available on-line at http://explorer.gavagai.seQC 20180306</p

The Gavagai Living Lexicon

This paper presents the Gavagai Living Lexicon, which is an online distributional semantic model currently available in 14 different languages. We describe the underlying distributional semantic model, and how we have solved some of the challenges in applying such a model to large amounts of streaming data. We also describe the architecture of our implementation, and discuss how we deal with continuous quality assurance of the lexicon.QC 20160610</p