This thesis investigates the design of sociable technologies and is divided into three main parts described below. In the first part, we introduce sociable technologies. We review our the definition of technology and propose categories of technologies according to the motivation underlying their design: improvement of control, improvement of communication or improvement of cooperation. Sociable technologies are then presented as an extension of techniques to improve cooperation. The design of sociable technologies are then discussed leading to the observation that acquisition of social common sense is a key challenge for designing sociable technologies. Finally, polite technologies are presented as an approach for acquiring social common sense. In the second part, we focus on the premises for the design of sociable technologies. A key aspect of social common sense is the ability to act appropriately in social situations. Associating appropriate behaviour with social situations is presented as a key method for implementing polite technologies. Reinforcement learning is proposed as a method for learning such associations and variation of this algorithm are experimentally evaluated. Learning the association between situation and behaviour relies on the strong assumption that mutual understanding of social situations can be achieved between technologies and people during interaction. We argue that in order to design sociable technologies, we must change the model of communication used by our technologies. We propose to replace the well-known code model of communication, with the ostensive-inferential model proposed by Sperber and Wilson. Hypotheses raised by this approach are evaluated in an experiment conducted in a smart environment, where, subjects by group of two or three are asked to collaborate with a smart environment in order to teach it how to behave in an automated meeting. A novel experimental methodology is presented: The Sorceress of Oz. The results collected from this experiment validate our hypothesis and provide insightful information for the design. We conclude by presenting, what we believe are, the premises for the design of sociable technologies. The final part of the thesis concerns an infrastructure for the design of sociable technologies. This infrastructure provides the support for three fundamental components. First, it provides the support for an inferential model of context. This inferential model of context is presented; a software architecture is proposed and evaluated in an experiment conducted in a smart-environment. Second, it provides the support for reasoning by analogy and introduces the concept of eigensituations. The advantage of this representation are discussed and evaluated in an experiment. Finally, it provides the support for ostensive-inferential communication and introduces the concept of ostensive interface.

University of Macau / Faculty of Social Sciences and Humanities / Department of English

This study mainly focuses on the emergence and utilization of communication systems in the context of joint action where collective cognitive activity is required. Dyads are given an instant messaging medium of communication where only a limited number of characters and symbols can be used for information exchange in order to collaborate on common tasks of finding objects, in a network-based interactive virtual environment (ActiveWorlds), a 3D, multi-agent, virtual reality platform. The restrictions on communication and the requirement of collaboration facilitated the creation of a lexical inventory and a minimalistic communication system, a compressed version of dyads&rsquo / shared Natural Languages (NLs). Across eight experimental sessions, two manipulations are made in order to study their effects on parameters on 4 levels of analysis: (1) Quantitative, (2) Syntactic Complexity, (3) Lexical Category and (4) Speech Act Category. The two interventions are (1) increasing the number of targets from one to two after the first three experiments, and (2) administering a two months break between the 6th and 7th-8th experiments. Increased number of target objects influenced the quantitative parameters that are related to the amount of communication as well as the use scores of lexical, syntactic, and speech act categories / however, the use ratios of several parameters were resilient under this manipulation and rather showed different trends of change characterizing the development of the system towards a more mature state in accordance with the demands of the task structure. The opposing trends of increasing use ratio of Assertive and decreasing use ratio of Directive Speech Acts and decreasing use ratios of the Type/Token Number of Lexical Items in a session, the Number of New Lexical Items in a session and increasing ratio of Turn Success are also characteristics of this maturation. The break administered between the 6th and 7th experimental session did not cause any decay in the acquired skills of using the emerged communication system. The previously negotiated strategies and acquired skills of communication as well as the trends of the use ratios of parameters were resilient. The qualitative analysis of the developing communication system revealed several strategies, including compression of NL words into new lexical items, exploiting the redundancy of characters of written words, and iconicity and indexicality of given symbols. The main drivers of the development of the new communication system appeared to be the processes of integration of communicative with behavioral action. The cognitive capacities enabling this integration and the comprehension of the utterances in the new system is explained by the Cognitive and Communicative Principles of Relevance that are attributed to a comprehension sub-module of a mind-reading module of the human cognitive system.

The aim of the study is to analyse the learning process of the Dorze weaving in Ethiopia and its implications on Education for Sustainable Development, ESD. My two main questions are: 1. How do the Dorze understand their learning process in weaving? 2. What conclusions concerning education for sustainable development applied on textile handicraft can be drawn from the findings of my case study?   In order to answer these questions I have made a field study on the Dorze (the weavers) in Addis Ababa in Ethiopia for 10 weeks. The study has a socio-cultural and narrative approach and the method used are interviews, observations and review of documents. The result is presented in a “metastory” where I retell the stories and introduce the results of the study and that gives answers to question 1. UNESCO’s recommendations on ESD are used to analyse the findings and give the answer to question 2. The result shows that the learning process depends on the environment with its people, who have gathered knowledge of raw material and techniques for generations but the latter also needs to develop to meet new challenges. “Shiro Meda” is the centre of learning. To grow up in “Shiro Meda” it becomes natural to work with textile production, accept a special lifestyle with clear gender differences and a hierarchical structure. The educational model of spinning and twisting are “learning by doing”, whereas young boys start practising weaving under the leadership of an older teacher step by step.   From an ESD perspective the Dorze education is holistic, practical, individualized, and contains some problem solving even if the students are not participating in decisions on how they learn. The education is highly integrated in the daily life of the weaving community and is also relevant to the surrounding local community. Moreover the education transfers a historical legacy of cultural continuity, and has shown itself to be dynamic and adaptable to change. A weakness in this traditional knowledge system is the low profit the weavers are making and the set hierarchical and gender rules which need to be developed in order to be sustainable for future challenges. The final discussion highlights the relevance of my findings for a Swedish learning context. / 2010ht4661

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This work aims at studying the effect of word position in text on understanding and tracking the content of written text. In this thesis we present two uses of word position in text: topic word selectors and topic flow signals. The topic word selectors identify important words, called <i>topic words</i>, by their spread through a text. The underlying assumption here is that words that repeat across the text are likely to be more relevant to the main topic of the text than ones that are concentrated in small segments. Our experiments show that manually selected keywords correspond more closely to topic words extracted using these selectors than to words chosen using more traditional indexing techniques. This correspondence indicates that topic words identify the topical content of the documents more than words selected using the traditional indexing measures that do not utilize word position in text. The second approach to applying word position is through <i>topic flow signals</i>. In this representation, words are replaced by the topics to which they refer. The flow of any one topic can then be traced throughout the document and viewed as a signal that rises when a word relevant to the topic is used and falls when an irrelevant word occurs. To reflect the flow of the topic in larger segments of text we use a simple smoothing technique. The resulting smoothed signals are shown to be correlated to the ideal topic flow signals for the same document. Finally, we characterize documents using the importance of their topic words and the spread of these words in the document. When incorporated into a Support Vector Machine classifier, this representation is shown to drastically reduce the vocabulary size and improve the classifier's performance compared to the traditional word-based, vector space representation.

Background: The concept of value perception is widely discussed in scientific literature and it is well-known, that channels deliver value to the customer. However, so far there has been no research about the efficiency of channels, especially the consumer´s perception of channel efficiency. Therefore, this study contributes to the current literature in channel management and it fills an existing research gap. The authors establish a definition of the term 'channel efficiency' and they develop a measuring instrument. For this thesis, the three criteria (1) shopping enjoyment, (2) interpersonal service quality and (3) price level are taken into consideration for the efficiency calculation. The two channels of interest are physical retail stores and the Internet. The target group is university students. Purpose: To measure and compare the efficiency of the channels 'physical retail store' and 'Internet' from the consumer´s view and thus, to find general patterns of rated channel efficiency. This will be achieved by investigating the individual channel value perception of certain channel specific criteria and by exploring the respective relevance of these criteria.   Research Questions: 1. What is the general channel efficiency of the channel physical retail store? 2. What is the general channel efficiency of the channel Internet? Method: A quantitative study in form of an online questionnaire has been conducted with German and Swedish students. 1 995 persons participated in the survey. The analysis has been carried out by using the computer software SPSS. Thus, the collected data could be edited with respect to the verification of the proposed hypotheses, the calculation and comparison of the respective channel efficiencies and additionally, the identification of patterns for gender and age groups. Research findings: The analysis of the collected data has shown that the three regarded criteria are of diverse importance and they are perceived differently for the channels physical retail stores and the Internet. Hence, the efficiency of those two channels is also unequal; physical retail stores reach a mean value of 46.8% and the Internet in turn achieves an average of 43.1%. This shows that both channels hold potential for improvement. When looking at patterns between gender and age groups, the authors could also identify interesting differentiations.

The increasing ubiquity of networked mobile devices such as cell phones and PDAs has created new opportunities for the transmission and display of multimedia content. However, any mobile device has inherent resource constraints: low network bandwidth, small screen sizes, limited input methods, and low commitment viewing. Mobile systems that provide information display and access thus need to mitigate these various constraints. Despite progress in information retrieval and content recommendation, there has been less focus on issues arising from a network-oriented and mobile perspective. This dissertation investigates a coordinated design approach to networked multimedia on mobile devices, and considers the abovementioned system perspectives. Within the context of accessing news video on mobile devices, the goal is to provide a cognitively palatable stream of videos and a seamless, low-latency user experience. Mixed-initiative---a method whereby intelligent services and users collaborate efficiently to achieve the user's goals, is the cornerstone of the system design and integrates user relevance feedback with a content recommendation engine and a content- and network-aware video buffer prefetching technique. These various components have otherwise been considered independently in other prior system designs. To overcome limited interactivity, a mixed-initiative user interface was used to present a sequence of news video clips to the user, along with operations to vote-up or vote-down a video to indicate its relevance. On-screen gesture equivalents of these operations were also implemented to reduce user interface elements occupying the screen. Semantic relevancy was then improved by extracting and indexing the content of each video clip as text features, and using a Na"ive Bayesian content recommendation strategy that harnessed the user relevance feedback to tailor the subsequent video recommendations. With the system's knowledge of relevant videos, a content-aware video buffer prefetching scheme was then integrated, using the abovementioned feedback to lower the user perceived latency on the client-end. As an information retrieval system consists of many interacting components, a client-server video streaming model is first developed for clarity and simplicity. Using a CNN news video clip database, experiments were then conducted using this model to simulate user scenarios. As the aim of improving semantic relevancy sometimes opposes user interface tools for interactivity and user perceived latency, a quantitative evaluation was done to observe the tradeoffs between bandwidth, semantic relevance, and user perceived latency. Performance tradeoffs involving semantic relevancy and user perceived latency were then predicted. In addition, complementary human user subjective tests are conducted with actual mobile phone hardware running on the Google Android platform. These experiments suggest that a mixed-initiative approach is helpful for recommending news video content on a mobile device for overcoming the mobile limitations of user interface tools for interactivity and client-end perceived latency. Users desired interactivity and responsiveness while viewing videos, and were willing to sacrifice some content relevancy in order gain lower perceived latency. Recommended future work includes expanding the content recommendation to incorporate viewing data from a large population, and the creation of a global hybrid content-based and collaborative filtering algorithm for better results. Also, based on existing user behaviour, users were reluctant to provide more input than necessary. Additional user experiments can be designed to quantify user attention and interest during video watching on a mobile device, and for better definition and incorporation of implicit user feedback.

<p>Chatroom conversations often elicit an initial impression of chaos. This is probably chiefly due to disrupted adjacency sequences, but also a result of the language being rich in non-standard linguistic forms and grammar. This study explores chatroom conversations with reference to Grice’s (1975) cooperative principle and the maxims that accompany it, and compares them to real life conversations. The aim is to see whether they differ from real life conversations to the extent expected, and whether these differences give rise to any compensational strategies to ensure successful communication. The results reveal a slightly higher amount of maxim undermining in the chat room than in the real life conversations, but not as high as expected. Accordingly, few compensational strategies need be adopted. It is suggested that the main explanation for these findings is that chatroom users have adapted their conversation patterns to the medium.</p>

傳統的音樂檢索系統主要在提供使用者特定音樂的查詢(target search)。除此之外，使用者也有類型音樂查詢(category search)的需求。在類型音樂查詢中，該類型的所有音都共同具備使用者所定義的概念(semantic concept)。這個由使用者定義的概念在音樂檢索系統上是主觀的且動態產生的。換句話說，同一使用者在不同情境之下對於同一首音樂可能產生不同的解讀概念。為了動態擷取使用者的概念，讓使用者參與在查詢過程的互動機制是必要的。因此， 我們提出將相關回饋(relevance feedback)的機制運用在以內容為主的音樂查詢系統上，讓系統從使用者的相關回饋中學習使用者的概念，並利用這學習出的概念來幫助音樂查詢。 由於使用者可能從整首音樂或音樂片段兩種角度來判斷該音樂是否具備使用者定義的概念。因此，本論文提出用以片段為主的音樂模型(segment-based modeling approach)將音樂表示成音樂片段的集合。進一步再從整首音樂和片段中擷取特徵。 其次，我們針對該問題提出相關演算法來探勘使用者的概念。該演算法先從相關和不相關的音樂資料庫中個別探勘常見樣式，再利用這些樣式建立分類器以區分音樂的相關性。 最後，我們分析各種系統回饋機制對搜尋效果的影響。Most-positive回傳機制會選擇根據目前系統判斷為最相關的物件。Most-informative機制則是回傳系統無法判斷其相關性的音樂物件。Most-informative 機制的目的在增加每回合系統從使用者身上得到的資訊量。Hybrid 則是中和前兩種機制的優點。本文中，我們模擬並比較各種回傳機制的效能。實驗結果顯示相關回饋機制確實能提升查詢的效果。 / Traditional content-based music retrieval system retrieves a specific music object which is similar to the user’s query. There is also a need, category search, for retrieving a specific category of music objects. In category search, music objects of the same category share a common semantic concept which is defined by the user. The concept for category search in music retrieval is subjective and dynamic. Different users at different time may have different interpretations for the same music object. In the music retrieval system along with relevance feedback mechanism, users are expected to be involved in the concept learning process. Relevance feedback enables the system to learn user’s concept dynamically. In this paper, the relevance feedback mechanism for category search of music retrieval based on the semantic concept learning is investigated. We proposed a segment-based music representation to assist the system in discovering user’s concept in terms of low-level music features. Each music object is modeled as a set of significant motivic patterns (SMP) achieved by discovering motivic repeating pattern. Both global and local music features are considered in concept learning. Moreover, to discover user’s semantic concept, a two-phase frequent pattern mining algorithm is proposed to discover common properties from relevant and irrelevant objects respectively and based on which a classifier is derived for distinguishing music objects. Except user’s feedback, three strategies of the system’s feedback to select objects for user’s relevance judgment are investigated. Most-positive strategy returns the most relevant music object to the user while most-informative strategy returns the most uncertain music objects for improving the discrimination power of the next round. Hybrid feedback strategy returns both of them. Comparative experiments are conducted to evaluate effectiveness of the proposed relevance feedback mechanism. Experimental results show that a better precision can be achieved via proposed relevance feedback mechanism.