scholarly journals Multimedia standards: building blocks of the Web

2001 ◽  
Vol 8 (3) ◽  
pp. 13-15
Author(s):  
L. Rutledge
Author(s):  
Michael Pradel ◽  
Jakob Henriksson ◽  
Uwe Aßmann

Although ontologies are gaining more and more acceptance, they are often not engineered in a component-based manner due to, among various reasons, a lack of appropriate constructs in current ontology languages. This hampers reuse and makes creating new ontologies from existing building blocks difficult. We propose to apply the notion of roles and role modeling to ontologies and present an extension of the Web Ontology Language OWL for this purpose. Ontological role models allow for clearly separating different concerns of a domain and constitute an intuitive reuse unit.


2020 ◽  
Author(s):  
Fahad Almusharraf ◽  
Jonathan Rose ◽  
Peter Selby

BACKGROUND At any given time, most smokers in a population are ambivalent with no motivation to quit. Motivational interviewing (MI) is an evidence-based technique that aims to elicit change in ambivalent smokers. MI practitioners are scarce and expensive, and smokers are difficult to reach. Smokers are potentially reachable through the web, and if an automated chatbot could emulate an MI conversation, it could form the basis of a low-cost and scalable intervention motivating smokers to quit. OBJECTIVE The primary goal of this study is to design, train, and test an automated MI-based chatbot capable of eliciting reflection in a conversation with cigarette smokers. This study describes the process of collecting training data to improve the chatbot’s ability to generate MI-oriented responses, particularly reflections and summary statements. The secondary goal of this study is to observe the effects on participants through voluntary feedback given after completing a conversation with the chatbot. METHODS An interdisciplinary collaboration between an MI expert and experts in computer engineering and natural language processing (NLP) co-designed the conversation and algorithms underlying the chatbot. A sample of 121 adult cigarette smokers in 11 successive groups were recruited from a web-based platform for a single-arm prospective iterative design study. The chatbot was designed to stimulate reflections on the pros and cons of smoking using MI’s running head start technique. Participants were also asked to confirm the chatbot’s classification of their free-form responses to measure the classification accuracy of the underlying NLP models. Each group provided responses that were used to train the chatbot for the next group. RESULTS A total of 6568 responses from 121 participants in 11 successive groups over 14 weeks were received. From these responses, we were able to isolate 21 unique reasons for and against smoking and the relative frequency of each. The gradual collection of responses as inputs and smoking reasons as labels over the 11 iterations improved the F1 score of the classification within the chatbot from 0.63 in the first group to 0.82 in the final group. The mean time spent by each participant interacting with the chatbot was 21.3 (SD 14.0) min (minimum 6.4 and maximum 89.2). We also found that 34.7% (42/121) of participants enjoyed the interaction with the chatbot, and 8.3% (10/121) of participants noted explicit smoking cessation benefits from the conversation in voluntary feedback that did not solicit this explicitly. CONCLUSIONS Recruiting ambivalent smokers through the web is a viable method to train a chatbot to increase accuracy in reflection and summary statements, the building blocks of MI. A new set of 21 <i>smoking reasons</i> (both for and against) has been identified. Initial feedback from smokers on the experience shows promise toward using it in an intervention.


10.2196/20251 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e20251
Author(s):  
Fahad Almusharraf ◽  
Jonathan Rose ◽  
Peter Selby

Background At any given time, most smokers in a population are ambivalent with no motivation to quit. Motivational interviewing (MI) is an evidence-based technique that aims to elicit change in ambivalent smokers. MI practitioners are scarce and expensive, and smokers are difficult to reach. Smokers are potentially reachable through the web, and if an automated chatbot could emulate an MI conversation, it could form the basis of a low-cost and scalable intervention motivating smokers to quit. Objective The primary goal of this study is to design, train, and test an automated MI-based chatbot capable of eliciting reflection in a conversation with cigarette smokers. This study describes the process of collecting training data to improve the chatbot’s ability to generate MI-oriented responses, particularly reflections and summary statements. The secondary goal of this study is to observe the effects on participants through voluntary feedback given after completing a conversation with the chatbot. Methods An interdisciplinary collaboration between an MI expert and experts in computer engineering and natural language processing (NLP) co-designed the conversation and algorithms underlying the chatbot. A sample of 121 adult cigarette smokers in 11 successive groups were recruited from a web-based platform for a single-arm prospective iterative design study. The chatbot was designed to stimulate reflections on the pros and cons of smoking using MI’s running head start technique. Participants were also asked to confirm the chatbot’s classification of their free-form responses to measure the classification accuracy of the underlying NLP models. Each group provided responses that were used to train the chatbot for the next group. Results A total of 6568 responses from 121 participants in 11 successive groups over 14 weeks were received. From these responses, we were able to isolate 21 unique reasons for and against smoking and the relative frequency of each. The gradual collection of responses as inputs and smoking reasons as labels over the 11 iterations improved the F1 score of the classification within the chatbot from 0.63 in the first group to 0.82 in the final group. The mean time spent by each participant interacting with the chatbot was 21.3 (SD 14.0) min (minimum 6.4 and maximum 89.2). We also found that 34.7% (42/121) of participants enjoyed the interaction with the chatbot, and 8.3% (10/121) of participants noted explicit smoking cessation benefits from the conversation in voluntary feedback that did not solicit this explicitly. Conclusions Recruiting ambivalent smokers through the web is a viable method to train a chatbot to increase accuracy in reflection and summary statements, the building blocks of MI. A new set of 21 smoking reasons (both for and against) has been identified. Initial feedback from smokers on the experience shows promise toward using it in an intervention.


Author(s):  
Giuliano Pistolesi

Synthetic Characters are intelligent agents able to show typical human-like cognitive behavior and an artificially-made perceived personality by means of complex natural language interaction and artificial reasoning and emotional skills. They are mainly spreading on the web as highly interactive digital assistants and tutoring agents on online database systems, e-commerce sites, web-based communities, online psychotherapy, and in several consulting situations where humans need assistance from intelligent software. Until now, synthetic characters, equipped with data, models, and simulation skills, have never been thought as the building blocks for natural language interaction-based intelligent DMSS. This chapter illustrates the first research and development attempt in this sense by an Open Source project in progress centred on the design of a synthetic character-based DMSS.


Author(s):  
Philippe De Ryck ◽  
Lieven Desmet ◽  
Frank Piessens ◽  
Martin Johns
Keyword(s):  

Author(s):  
Fernando Reinaldo Ribeiro ◽  
Rui José

A public display that is able to present the right information at the right time is a very compelling concept. However, realising or even approaching this ability to autonomously select appropriate content based on some interpretation of the surrounding social context represents a major challenge. This chapter provides an overview of the key challenges involved and an exploration of some of the main alternatives available. It also describes a novel content adaptation framework that defines the key building blocks for supporting autonomous selection of the Web sources for presentation on public displays. This framework is based on a place model that combines content suggestions expressed by multiple place visitors with those expressed by the place owner. Evaluation results have shown that a place tag cloud can provide a valuable approach to this issue and that people recognize and understand the sensitivity of the system to their demands.


Author(s):  
Mark D. Niemiec

Life, like many other cellular automata, contains many interesting objects, such as still lifes, oscillators, spaceships, spaceship guns, puffer trains, breeders, and the like. While many of these, like blocks, blinkers, and gliders, occur naturally with great frequency, there are many others that occur infrequently, and countless others that have never yet been observed in any natural context. This chapter deals with methods for synthesizing such complex objects from simple building blocks, such as gliders or other easy-to-synthesize objects. Once an object can be shown to be built in this manner, the object may be used as a building block in larger relocatable structures, such as Turing machines or universal constructors. In addition, the existence of a natural synthesis of an object from a bounded number of gliders implies that the object will form naturally in a sufficiently large, sufficiently sparse field [2]. Inasmuch as this chapter deals mainly with practical aspects of object synthesis, rather than theoretical ones, it may resemble a talk on chemical engineering, rather than abstract mathematics. All figures shown here, unless otherwise specified, show “before” and “after” images of collision sequences; the “before” sequences are shown on the left with dark cells, and the “after” sequences to the right of them in lighter cells. In some cases, unwanted debris is also generated and must be removed later; this debris is shown in the lightest color. There are several basic ways in which objects can be synthesized. The most common objects occur in great abundance in nature, so there are many random collisions of a small number of gliders that will produce them. There have been many random broth experiments conducted in Life, in which fields initialized to random initial configurations have been run until they became periodic, and then the resulting ash analyzed. The results of two such series of experiments, performed by Achim Flammenkamp [1] and Heinrich Koenig [3], are available on the Web. If the objects are sorted in order of decreasing frequency of natural occurrence, the list is also in order of increasing synthesis cost in gliders (with a few rare objects out of place).


Author(s):  
Mohammad Moradi ◽  
MohammadReza Keyvanpour

Since the early days of introducing eXtensible Markup Language (XML), owing to its expressive capabilities and flexibilities, it became the defacto standard for representing, storing, and interchanging data on the Web. Such features have made XML one of the building blocks of the Semantic Web. From another viewpoint, since XML documents could be considered from content, structural, and semantic aspects, leveraging their semantics is very useful and applicable in different domains. However, XML does not by itself introduce any built-in mechanisms for governing semantics. For this reason, many studies have been conducted on the representation of semantics within/from XML documents. This paper studies and discusses different aspects of the mentioned topic in the form of an overview with an emphasis on the state of semantics in XML and its presentation methods.


2009 ◽  
Vol 4 (1) ◽  
pp. 107-124 ◽  
Author(s):  
Amanda Spencer ◽  
John Sheridan ◽  
David Thomas ◽  
David Pullinger

Government's use of the Web in the UK is prolific and a wide range of services are now available though this channel. The government set out to address the problem that links from Hansard (the transcripts of Parliamentary debates) were not maintained over time and that therefore there was need for some long-term storage and stewardship of information, including maintaining access. Further investigation revealed that linking was key, not only in maintaining access to information, but also to the discovery of information. This resulted in a project that affects the entire  government Web estate, with a solution leveraging the basic building blocks of the Internet (DNS) and the Web (HTTP and URIs) in a pragmatic way, to ensure that an infrastructure is in place to provide access to important information both now and in the future.


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