ShopWithMe!: Collaborative Information Searching and Shopping for Online Retail

We present research on the development and evaluation of a collaborative search and shopping system for online retail tasks based on domain specific product requirements. We describe the design rationale for the system development and inclusion of collaborative features, including search, chat, clip-board, product suggestions, shared views, and shopping cart with a focus on how these features are used for collaborative online retail shopping and information searching and sharing. Our research goal is to understand whether collaborative search tools are useful in supporting actual collaborative online retail shopping tasks for experience goods. We describe system development and report findings from preliminary user studies of the system, using mixed methods analysis, with an emphasis on the qualitative findings. The findings highlight that systems for the online shopping domain can support searching, shared views, and group communication to aid in collaborative shopping for experience goods by improving information sharing among group members. Implications are that ecommerce systems, websites, and web apps should support collaboration based on product types

Unterstützung und Implikationen von Gruppen-Awareness bei einer kollaborativen Websuche

In den letzten Jahren wurden zahlreiche Anwendungen entwickelt, um kollaborative Websuchen über größere Entfernungen hinweg zu unterstützen. Es wurde gezeigt, dass Gruppen-Awareness einen bedeutenden Einfluss auf den Erfolg entsprechender Anwendungen hat. Obwohl kollaborative Websuchen häufig auch an einem lokalen Ort stattfinden, wurde dieses Szenario in aktuellen Arbeiten deutlich weniger betrachtet. In dieser Masterarbeit wird der Einfluss von Gruppen-Awareness auf lokale kollaborative Websuche in Kleingruppen untersucht. Ein Schwerpunkt liegt dabei auf der Unterscheidung zwischen Anwendungen für lokale Websuche und solchen, bei denen sich die Teilnehmer*innen an unterschiedlichen Orten befinden. Bestehende Anwendungen für kollaborative Websuchen werden vorgestellt und eingeordnet. Basierend auf einem neu vorgestellten Prototypen wird eine Pilotstudie in einer Multi-Device-Umgebung durchgeführt. Die Studie zeigt, dass sich die Bereitstellung von Aktivitätsdaten positiv auf die Arbeitsergebnisse von lokalen kollaborativen Websuchen auswirken kann. Zudem wurden Schwachstellen und Verbesserungsmöglichkeiten für die bestehenden Funktionen identifiziert.:1 Einleitung 1 1.1 Motivation 1 1.2 Zielstellung und Aufbau 2 2 Forschungsstand 5 2.1 Kollaboration 5 2.2 Gruppen-Awareness 7 2.3 Kollaborative Websuche 9 2.3.1 Sensemaking 11 2.3.2 Lokale Websuche 13 2.3.3 Suchstrategien 16 2.4 Cross-Device-Websuche 18 2.5 Anwendungen für kollaborative Websuche 19 2.5.1 Anwendungen für Websuchen an unterschiedlichen Orten 20 2.5.2 Anwendungen für lokale Websuchen 25 2.6 Zusammenfassung des Forschungsstandes 28 3 CoFind 31 3.1 Ansichten und Funktionen 32 3.1.1 Sidebar 33 3.1.2 Detailansicht 37 3.1.3 Modi 39 3.1.4 Einschränkungen 41 3.2 Logging 42 3.2.1 Nutzerbezogene Logs 43 3.2.2 Laufzeitbezogene Logs 43 3.3 Architektur 44 3.3.1 Kommunikation und Websockets 44 3.3.2 Client 44 3.3.3 Server 45 3.3.4 Datenbank 46 3.3.5 Konfiguration 47 3.4 Zusammenfassung 48 4 Nutzerstudie 51 4.1 Aufgabenstellung 51 4.2 Studiendesign 52 4.2.1 Aufbau 52 4.2.2 Geräte und Software 53 4.2.3 Anforderungen an die Teilnehmer 55 4.2.4 Methodik 56 4.3 Datenerhebung 57 5 Ergebnisse 63 5.1 Teilnehmer 63 5.2 Arbeitsergebnisse 65 5.3 Gruppenarbeit und Kollaboration 66 5.3.1 Raumnutzung 66 5.3.2 Arbeitsphasen 67 5.3.3 Kommunikation 69 5.3.4 Nutzung der Hardware 70 5.4 CoFind und Gruppen-Awareness 72 5.4.1 Allgemeiner Eindruck 72 5.4.2 Nutzung des CoFind-Plug-ins 73 5.4.3 Sidebar 76 5.4.4 Detailansicht 78 5.4.5 Sicherheit 79 5.5 Diskussion 79 5.5.1 Bewertung des Studiendesigns 80 5.5.2 Bewertung des CoFind-Plug-ins 81 5.5.3 Diskussion der Forschungsfragen 84 6 Fazit 87 6.1 Zusammenfassung 87 6.2 Ausblick 88 Literatur 91 A Anhang 103In recent years, numerous applications have been developed to support collaborative web search over large distances. A major impact of group awareness on the success of such applications has been shown. Although collaborative web search often occurs co-located, this scenario is underrepresented in recent studies. This master thesis investigates the influence of group awareness on co-located collaborative web search in small groups is investigated. ThIt focuses on a distinction between tools for remote and co-located web search. Existing applications for collaborative web search are presented and classified. Based on a new prototype a pilot study in a multi device environment is conducted. The study shows a positive effect on co-located collaborative web search by providing activity data among groups. In addition, weaknesses and opportunities to improve existing functions are shown.:1 Einleitung 1 1.1 Motivation 1 1.2 Zielstellung und Aufbau 2 2 Forschungsstand 5 2.1 Kollaboration 5 2.2 Gruppen-Awareness 7 2.3 Kollaborative Websuche 9 2.3.1 Sensemaking 11 2.3.2 Lokale Websuche 13 2.3.3 Suchstrategien 16 2.4 Cross-Device-Websuche 18 2.5 Anwendungen für kollaborative Websuche 19 2.5.1 Anwendungen für Websuchen an unterschiedlichen Orten 20 2.5.2 Anwendungen für lokale Websuchen 25 2.6 Zusammenfassung des Forschungsstandes 28 3 CoFind 31 3.1 Ansichten und Funktionen 32 3.1.1 Sidebar 33 3.1.2 Detailansicht 37 3.1.3 Modi 39 3.1.4 Einschränkungen 41 3.2 Logging 42 3.2.1 Nutzerbezogene Logs 43 3.2.2 Laufzeitbezogene Logs 43 3.3 Architektur 44 3.3.1 Kommunikation und Websockets 44 3.3.2 Client 44 3.3.3 Server 45 3.3.4 Datenbank 46 3.3.5 Konfiguration 47 3.4 Zusammenfassung 48 4 Nutzerstudie 51 4.1 Aufgabenstellung 51 4.2 Studiendesign 52 4.2.1 Aufbau 52 4.2.2 Geräte und Software 53 4.2.3 Anforderungen an die Teilnehmer 55 4.2.4 Methodik 56 4.3 Datenerhebung 57 5 Ergebnisse 63 5.1 Teilnehmer 63 5.2 Arbeitsergebnisse 65 5.3 Gruppenarbeit und Kollaboration 66 5.3.1 Raumnutzung 66 5.3.2 Arbeitsphasen 67 5.3.3 Kommunikation 69 5.3.4 Nutzung der Hardware 70 5.4 CoFind und Gruppen-Awareness 72 5.4.1 Allgemeiner Eindruck 72 5.4.2 Nutzung des CoFind-Plug-ins 73 5.4.3 Sidebar 76 5.4.4 Detailansicht 78 5.4.5 Sicherheit 79 5.5 Diskussion 79 5.5.1 Bewertung des Studiendesigns 80 5.5.2 Bewertung des CoFind-Plug-ins 81 5.5.3 Diskussion der Forschungsfragen 84 6 Fazit 87 6.1 Zusammenfassung 87 6.2 Ausblick 88 Literatur 91 A Anhang 10

Design and creation of interactive and manipulative activities for learning university calculus

RESUMEN. Muchos de los estudiantes de primer curso de Universidad encuentran dificultades en la comprensión y utilización de los conceptos matemáticos con los que se trabajan en las asignaturas de Cálculo de los Grados del área de Ciencias e Ingeniería. La enseñanza con tecnología facilita explorar nuevas posibilidades tanto en la comprensión de conceptos teóricos como aplicados al permitir mostrar e interactuar con la información de forma distinta a la que es posible con los tradicionales libros de texto. Este artículo presenta una propuesta de un grupo de profesores de la Universidad de Cantabria que utiliza la web para plantear nuevas metodologías de aprendizaje que estimulen y orienten al estudiante para lograr una mayor autonomía en su progreso académico. Con este fin, se han desarrollado actividades manipulativas e interactivas para promover el trabajo personal del alumno, la utilización de software matemático y las posibilidades multimedia que ofrece la web. Se describe también la experimentación realizada con estas actividades en los cursos 2011-12 y 2012-13 en las asignaturas de Cálculo de los Grados que se imparten en la Escuela de Ingenieros Industriales y Telecomunicación de la Universidad de Cantabria.ABSTRACT. Many first year university students encounter difficulties in understanding the mathematical concepts which are used in Calculus courses in the Science and Engineering Degrees. Teaching with technology allows for new possibilities both in the understanding of theoretical and applied concepts which allows for information to be shown and interacted with in a way that is distinct from traditional textbooks. This article presents a proposal by a group of professors from the University of Cantabria which utilizes the internet to set out new learning methodologies that stimulate and orient the student to achieve greater autonomy in his or her academic progress. To this end, manipulative and interactive activities have been developed which intend to promote the students’ personal work, the use of mathematical software and the multimedia possibilities offered online. It also describes the experience brought forth with these activities in the academic courses of 2011-12 and 2012-13 in the Calculus courses in the Degrees taught in the School of Industrial Engineering and Telecommunications of the University of Cantabria

Design and Implementation of the Results Space project into Android OS

This paper describes the design and implementation of an application of the Results Space project into an Android powered mobile cell phone. Results Space is an NSF-sponsored project started in the fall of 2008 that is part of the Interaction Design Lab at the School of Information and Library Science at the University of North Carolina at Chapel Hill. Results Space aims to improve the efficiency of searching through the web by providing a framework that focuses on organizing search results and providing easier collaboration amongst the users within the same search domain. The mobile version of Results Space aims to be a quick interface where a user can scan through subscribed projects, view updates and browse through the result sets of each project. Thus, the mobile version becomes mainly a tool for viewing and not manipulating data. Finally, this paper introduces the recently released Google cell phone platform, named Android. It describes the steps for developing the Results Space mobile edition as well as discussing the challenges and their resolution during the development process

Characterizing and Understanding User Perception of System Initiative for Conversational Systems to Support Collaborative Search

Popular messaging applications such as Slack, Discord, and Microsoft Teams have given rise to thousands of chatbots and in-app integrations to facilitate collaborations. We utilized this design framework to study how searchbots (i.e., chatbots that perform specific searches) can facilitate collaborative search. More specifically, we investigated a design space for searchbot's that can engage in a mixed-initiative interaction. In this dissertation, we present a Wizard of Oz (WoZ) study to investigate the implications of envisioning a conversational search system capable of engaging in mixed-initiative interactions to support collaborative search. The Wizard plays the role of a conversational search system that can search for information, send relevant web results, and message users. We investigated three Wizard conditions: bot\_info, bot\_dialog, and bot\_task, which differ in how the Wizard can intervene in a conversation. The intervention modes follow the mixed-initiative framework by ~\cite{chu1998evidential}, originally developed based on human conversations. Broadly, we report on three investigations: (1) participants perceptions of the searchbot across the different levels of inititive; (2) the Wizards' motivations to take the initiative; and (3) the Wizards' characterization of the appropriateness of their interventions. Our results suggest that participants' collaborations can enhance when the searchbot can take limited initiative and align with the participants' search strategy. Additionally, in the characterization of motivations and timings, the Wizard presented a wide array of themes to provide search assistance and promote collaborations. Finally, while the participants did not prefer the advanced capabilities of the searchbot, our characterization of their motivations and timing helps us understand the complex activities the searchbot can cater to support collaborations.Doctor of Philosoph

Online Personalization in Exploratory Search

Modern society produces vast amounts of digital data related to multiple domains of our lives. We produce data in our free time when browsing the net or taking photos with various personal devices, such as phones or ipads. Businesses and governments also gather a lot of information related to our interests, habits or otherwise personal information (legal status, health data, etc.). The amount of data produced is growning too large for us to be handled manually, and so to assist the user, specialized information retrieval systems have been developed to allow efficient perusal of different types of data. Unfortunately, as using such systems often requires expert understanding of the domain in question, many users get lost in their attempt to navigate the search space. This problem will only be exacerbated in the future, as the amount of data keeps growing, giving us less time to learn about the domains involved. Exploratory search is a field of research that studies user behaviour in situations, where users have little familiarity with the search domain, or have not yet decided exactly what their search goal is. Situations such as these arise when the user wishes to explore what is available, or is otherwise synthesizing or investigating the data. To assist the user in exploratory search and in finding relevant information, various methodologies may be employed, such as user modeling techniques or novel interfaces and data visualization techniques. This thesis presents exploratory search techniques for online personalization and feature representations that allow efficient perusal of unknown datasets. These methods are showcased in two different search environments. First, we present a search engine for scientific document retrieval, which takes the user's knowledge level into account in order to provide the user with more or less diverse search results. The second search environment aims at supporting the user when browsing through a dataset of unannotated images. Overall, the research presented here describes a number of techniques based on reinforcement learning and neural networks that, compared to traditional search engines, can provide better support for users who are unsure of the final goal of their search or who cannot easily formulate their search needs.Moderni yhteiskunta tuottaa suuria määriä digitaalista dataa liittyen elämämme eri osa-alueisiin. Tuotamme tätä dataa vapaa-ajallamme kun käymme internetissä, tai tuotamme moninaista multimediaa eri älylaitteillamme. Tämä näkyy vahvasti myös yritysten liiketoiminnassa ja valtioiden hallinnassa, missä erilaisten toimintojen seurantaa kirjataan digitaalisesti, kuten laillisen informaation, terveysdatan ja henkilökohtaisen datan muodossa. Tuotetun datan määrä on kasvamassa liian suureksi yksittäisten ihmisten käsiteltäväksi, ja täten järjestelmiä mitkä automatisoivat hakuprosessia tuotetaan enenevässä määrin. Valitettavasti, useat näistä järjestelmistä vaativat asiantuntemusta annetulta alalta, minkä takia käyttäjät eksyvät helposti hakuavaruuteen. Exploratiivinen haku on tieteenala joka tutkii käyttäjän käyttäytyymistä tilanteissa, missä heillä on vähän tuntemusta alalta, tai he eivät ole vielä päättäneet mikä on heidän hakunsa päämäärä. Tällaiset tilanteet syntyvät kun käyttäjä haluaa kartoittaa saatavilla olevaa aineistoa, tai muuten syntetisoida tai tutkia kyseistä dataa. Oleellisen tiedon löytämiseksi exploratiivinen haku hyödyntää erilaisia menetelmiä, kuten käyttäjän mallintamista, erikoisia käyttöliittymiä tai datan visualisointimenetelmiä. Tämä kirja esittelee exploratiivisen haun menetelmiä ajantasaiseen personalisointiin ja piirrerepresentaatioihin, mitkä mahdollistavat käyttäjälle entuudestaan tuntemattomien tietokantojen tehokkaan käsittelyn. Nämä menetelmät esitellään kahden hakujärjestelmän yhteydessä. Ensiksi, esittelemme hakukoneen tieteellisille artikkeleille, mikä ottaa käyttäjän tietotason huomioon kun hakutuloksia esitellään. Jälkimmäinen hakukone mahdollistaa annotoimattomien kuvien tehokkaan selailun. Kokonaisuudessaan, tämä kirja kertoo useasta tutkimus- ja järjestelmämenetelmästä, mitkä, verrattuna perinteisiin hakukoneisiin, tukevat epävarman käyttäjän hakuprosessia tuntemattomassa ympäristössä paremmin

Exposing concurrency failures: a comprehensive survey of the state of the art and a novel approach to reproduce field failures

With the rapid advance of multi-core and distributed architectures, concurrent systems are becoming more and more popular. Concurrent systems are extremely hard to develop and validate, as their overall behavior depends on the non-deterministic interleaving of the execution flows that comprise the system. Wrong and unexpected interleavings may lead to concurrency faults that are extremely hard to avoid, detect, and fix due to their non-deterministic nature. This thesis addresses the problem of exposing concurrency failures. Exposing concurrency failures is a crucial activity to locate and fix the related fault and amounts to determine both a test case and an interleaving that trigger the failure. Given the high cost of manually identifying a failure-inducing test case and interleaving among the infinite number of inputs and interleavings of the system, the problem of automatically exposing concurrency failures has been studied by researchers since the late seventies and is still a hot research topic. This thesis advances the research in exposing concurrency failures by proposing two main contributions. The first contribution is a comprehensive survey and taxonomy of the state-of-the-art techniques for exposing concurrency failures. The taxonomy and survey provide a framework that captures the key features of the existing techniques, identify a set of classification criteria to review and compare them, and highlight their strengths and weaknesses, leading to a thorough assessment of the field and paving the road for future progresses. The second contribution of this thesis is a technique to automatically expose and reproduce concurrency field failure. One of the main findings of our survey is that automatically reproducing concurrency field failures is still an open problem, as the few techniques that have been proposed rely on information that may be hard to collect, and identify failure-inducing interleavings but do not synthesize failure-inducing test cases. We propose a technique that advances over state- of-the-art approaches by relying on information that is easily obtainable and by automatically identifying both a failure- inducing test case and interleaving. We empirically demonstrate the effectiveness of our approach on a benchmark of real concurrency failures taken from different popular code bases

Dynamics of Long-Life Assets: From Technology Adaptation to Upgrading the Business Model

Knowledge management; Business information system

Improving the fidelity of abstract camera network simulations

This thesis studies the impact of augmenting an abstract target detection model with a higher degree of realism on the fidelity of the outcomes of camera network simulators in reflecting real-world results. The work is motivated by the identified trade-off between realistic but computationally expensive models and approximate but computationally cheap models. This trade-off opens the possibility for an al-ternative to augment abstract simulation tools with a higher degree of realism to capture both benefits, low computational expense with a higher fidelity of the out-comes. For the task of target detection, we propose a novel decomposition method with an intermediate point of representation. This point is the core element of our model that decouples the architecture into two parts. Decoupling brings flexibility and modularity into the design. This empowers practitioners to select the model’s fea-tures individually and independently to their requirements and camera settings. To investigate the fidelity of our model’s outcomes, we build models of three detectors and apply on our lab-based image data set to create ground truth confidences. By incorporating only a few more properties of realism, the fidelity of our model’s out-comes improved significantly when compared to the initial results in reflecting the ground truth confidences. Finally, to explore the implication of our high fidelity target detection model, we select a case study from coverage redundancy in smart camera networks. High-lighting the performance of a coverage approach strongly relies on the reliability of target detection results. An underestimation in the performance of studied coverage approaches is determined by employing the standard abstract detection model when compared to the results of our model. The identified underestimation in this study is one example of the general open concern in agent-based modelling about the unclear impact of simplified abstract models on the ability of the simulator to capture real-world behaviours