A context-sensitive conceptual framework for activity modeling

Human motion trajectories, however captured, provide a rich spatiotemporal data source for human activity recognition, and the rich literature in motion trajectory analysis provides the tools to bridge the gap between this data and its semantic interpretation. But activity is an ambiguous term across research communities. For example, in urban transport research activities are generally characterized around certain locations assuming the opportunities and resources are present in that location, and traveling happens between these locations for activity participation, i.e., travel is not an activity, rather a mean to overcome spatial constraints. In contrast, in human-computer interaction (HCI) research and in computer vision research activities taking place along the way, such as reading on the bus, are significant for contextualized service provision. Similarly activities at coarser spatial and temporal granularity, e.g., holidaying in a country, could be recognized in some context or domain. Thus the context prevalent in the literature does not provide a precise and consistent definition of activity, in particular in differentiation to travel when it comes to motion trajectory analysis. Hence in this paper, a thorough literature review studies activity from different perspectives, and develop a common framework to model and reason human behavior flexibly across contexts. This spatio-temporal framework is conceptualized with a focus on modeling activities hierarchically. Three case studies will illustrate how the semantics of the term activity changes based on scale and context. They provide evidence that the framework holds over different domains. In turn, the framework will help developing various applications and services that are aware of the broad spectrum of the term activity across contexts

Post-processing of association rules.

In this paper, we situate and motivate the need for a post-processing phase to the association rule mining algorithm when plugged into the knowledge discovery in databases process. Major research effort has already been devoted to optimising the initially proposed mining algorithms. When it comes to effectively extrapolating the most interesting knowledge nuggets from the standard output of these algorithms, one is faced with an extreme challenge, since it is not uncommon to be confronted with a vast amount of association rules after running the algorithms. The sheer multitude of generated rules often clouds the perception of the interpreters. Rightful assessment of the usefulness of the generated output introduces the need to effectively deal with different forms of data redundancy and data being plainly uninteresting. In order to do so, we will give a tentative overview of some of the main post-processing tasks, taking into account the efforts that have already been reported in the literature.

Adaptation “in the Wild”: Ontology-Based Personalization of Open-Corpus Learning Material

Abstract. Teacher and students can use WWW as a limitless source of learning material for nearly any subject. Yet, such abundance of content comes with the problem of finding the right piece at the right time. Conventional adaptive educational systems cannot support personalized access to open-corpus learning material as they rely on manually constructed content models. This paper presents an approach to this problem that does not require intervention from a human expert. The approach has been implemented in an adaptive system that recommends students supplementary reading material and adaptively annotates it. The results of the evaluation experiment have demonstrated several significant effects of using the system on students ’ learning

Adaptation “in the Wild”: Ontology-Based Personalization of Open-Corpus Learning Material

Teacher and students can use WWW as a limitless source of learning material for nearly any subject. Yet, such abundance of content comes with the problem of finding the right piece at the right time. Conventional adaptive educational systems cannot support personalized access to open-corpus learning material as they rely on manually constructed content models. This paper presents an approach to this problem that does not require intervention from a human expert. The approach has been implemented in an adaptive system that recommends students supplementary reading material and adaptively annotates it. The results of the evaluation experiment have demonstrated several significant effects of using the system on students’ learning.\u

Mastering the requirements analysis for communication-intensive websites

Web application development still needs to employ effective methods to accommodate some distinctive aspects of the requirements analysis process: capturing high-level communication goals, considering several user profiles and stakeholders, defining hypermedia-specific requirements (concerning navigation, content, information structure and presentation aspects), and reusing requirements for an effective usability evaluation. Techniques should be usable by both stakeholders and the design team, require little training effort, and show relative advantage to project managers. Over the last few years, requirements methodologies applied to web-based applications have considered mainly the transactional and operational aspects typical of traditional information systems. The communicational aspects of web sites have been neglected in regards to systematic requirements methods. This thesis, starting from key achievements in Requirements Engineering (hereafter RE), introduces a model (AWARE) for defining and analyzing requirements for web applications mainly conceived as strategic communication means for an institution or organization. The model extends traditional goal and scenario-based approaches for refining highlevel goals into website requirements, by introducing the analysis of ill-defined user goals, stakeholder communication goals, and a hypermedia requirement taxonomy to facilitate web conceptual design, and paving the way for a systematic usability evaluation. AWARE comprises a conceptual toolkit and a notation for effective requirements documentation. AWARE concepts and notation represent a useful communication and analysis conceptual tool that may support in the elicitation, negotiation, analysis and validation of requirements from the relevant stakeholders (users included). The empirical validation of the model is carried out in two ways. Firstly, the model has been employed in web projects on the field. These case studies and the lessons learnt will be presented and discussed to assess advantages and limits of the proposal. Secondly, a sample of web analysts and designers has been asked to study and apply the model: the feedback gathered is positive and encouraging for further improvement.Lo sviluppo di applicazioni web necessita di strumenti efficaci per gestire alcuni aspetti essenziali del processo di analisi dei requisiti: l'identificazione di obiettivi di comunicazione strategici, la presenza di una varietà di profili utente e di stakeholders, le definizione di requisiti ipermediali (riguardanti navigazione, interazione, contenuto e presentazione), e il riuso dei requisiti per una pianificazione efficace della valutazione dell'usabilità. Sono necessarie tecniche usabili sia dagli stakeholders che dai progettisti, che richiedono un tempo breve per essere appresi ed usati con efficacia, mostrando vantaggi significativi ai gestori di progetti complessi. La tesi definisce AWARE (Analysis of Web Application Requirements) - una metodologia per l'analisi dei requisiti specifica per la gestione di siti web (ed applicazioni interattive) con forti componenti comunicative. La metodologia estende le tecniche esistenti dell''analisi dei requisiti basate su approcci goal-oriented e scenario-based, introducendo una tassonomia di requisiti specifica per siti web (che permette di dare un input strutturato all'attività di progetazione), strumenti per l'identificazione e l'analisi di obiettivi ill-defined (generici o mal-definiti) e di obiettivi comunicativi e supporto metodologico per la valutazione dell'usabilità basata sui requisiti dell'applicazione. La metodologia AWARE è stata valutata sul campo attraverso progetti con professionisti del settore (web designers e IT managers), e grazie ad interventi di formazione in aziende specializzate nella comunicazione su web

Combining relevance information in a synchronous collaborative information retrieval environment

Traditionally information retrieval (IR) research has focussed on a single user interaction modality, where a user searches to satisfy an information need. Recent advances in both web technologies, such as the sociable web of Web 2.0, and computer hardware, such as tabletop interface devices, have enabled multiple users to collaborate on many computer-related tasks. Due to these advances there is an increasing need to support two or more users searching together at the same time, in order to satisfy a shared information need, which we refer to as Synchronous Collaborative Information Retrieval. Synchronous Collaborative Information Retrieval (SCIR) represents a significant paradigmatic shift from traditional IR systems. In order to support an effective SCIR search, new techniques are required to coordinate users' activities. In this chapter we explore the effectiveness of a sharing of knowledge policy on a collaborating group. Sharing of knowledge refers to the process of passing relevance information across users, if one user finds items of relevance to the search task then the group should benefit in the form of improved ranked lists returned to each searcher. In order to evaluate the proposed techniques we simulate two users searching together through an incremental feedback system. The simulation assumes that users decide on an initial query with which to begin the collaborative search and proceed through the search by providing relevance judgments to the system and receiving a new ranked list. In order to populate these simulations we extract data from the interaction logs of various experimental IR systems from previous Text REtrieval Conference (TREC) workshops