GLR-Parsing of Word Lattices Using a Beam Search Method

This paper presents an approach that allows the efficient integration of speech recognition and language understanding using Tomita's generalized LR-parsing algorithm. For this purpose the GLRP-algorithm is revised so that an agenda mechanism can be used to control the flow of computation of the parsing process. This new approach is used to integrate speech recognition and speech understanding incrementally with a beam search method. These considerations have been implemented and tested on ten word lattices.Comment: 4 pages, 61K postscript, compressed, uuencoded, Eurospeech 9/95, Madri

Social Web Communities

Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software

Social Web Communities

Blogs, Wikis, and Social Bookmark Tools have rapidly emerged onthe Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software

Linked data querying through FCA-based schema indexing

The efficiency of SPARQL query evaluation against Linked Open Data may benefit from schema-based indexing. However, many data items come with incomplete schema information or lack schema descriptions entirely. In this position paper, we outline an approach to an indexing of linked data graphs based on schemata induced through Formal Concept Analysis. We show how to map queries onto RDF graphs based on such derived schema information. We sketch next steps for realizing and optimizing the suggested approach

Analyzing the Impact of Cognitive Load in Evaluating Gaze-based Typing

Gaze-based virtual keyboards provide an effective interface for text entry by eye movements. The efficiency and usability of these keyboards have traditionally been evaluated with conventional text entry performance measures such as words per minute, keystrokes per character, backspace usage, etc. However, in comparison to the traditional text entry approaches, gaze-based typing involves natural eye movements that are highly correlated with human brain cognition. Employing eye gaze as an input could lead to excessive mental demand, and in this work we argue the need to include cognitive load as an eye typing evaluation measure. We evaluate three variations of gaze-based virtual keyboards, which implement variable designs in terms of word suggestion positioning. The conventional text entry metrics indicate no significant difference in the performance of the different keyboard designs. However, STFT (Short-time Fourier Transform) based analysis of EEG signals indicate variances in the mental workload of participants while interacting with these designs. Moreover, the EEG analysis provides insights into the user's cognition variation for different typing phases and intervals, which should be considered in order to improve eye typing usability.Comment: 6 pages, 4 figures, IEEE CBMS 201

СТАРИЙ ЗАВІТ ЯК ДЖЕРЕЛО ХРИСТИЯНСЬКИХ СИМВОЛІЧНИХ ТОПОСІВ

У статті досліджено старозавітна генеза християнської символіки. Проаналізовано вплив юдейських текстів на формування теологічної символіки таїнства хрещення. Розглянуто континуальність біблійної семіосфери жертвопринесень: від старозавітних жертв до новозавітної євхаристії. З’ясовано, що теологічна спадкоємність Старого й Нового Завітів передбачає успадкування християнством із юдаїзму образно-символічних топосів у парадигмі "традиція-новаторство", відповідно до новозавітної сотеріології. Зроблено висновок, що органічний взаємозв'язок двох частин Біблії прослідковується не тільки на теологічному рівні, але й на структурно-семіотичному рівні

Emotional Framing in the Spreading of False and True Claims

The explosive growth of online misinformation, such as false claims, has affected the social behavior of online users. In order to be persuasive and mislead the audience, false claims are made to trigger emotions in their audience. This paper contributes to understanding how misinformation in social media is shaped by investigating the emotional framing that authors of the claims try to create for their audience. We investigate how, firstly, the existence of emotional framing in the claims depends on the topic and credibility of the claims. Secondly, we explore how emotionally framed content triggers emotional response posts by social media users, and how emotions expressed in claims and corresponding users' response posts affect their sharing behavior on social media. Analysis of four data sets covering different topics (politics, health, Syrian war, and COVID-19) reveals that authors shape their claims depending on the topic area to pass targeted emotions to their audience. By analysing responses to claims, we show that the credibility of the claim influences the distribution of emotions that the claim incites in its audience. Moreover, our analysis shows that emotions expressed in the claims are repeated in the users' responses. Finally, the analysis of users' sharing behavior shows that negative emotional framing such as anger, fear, and sadness of false claims leads to more interaction among users than positive emotions. This analysis also reveals that in the claims that trigger happy responses, true claims result in more sharing compared to false claims