Diverse Contributions to Implicit Human-Computer Interaction

Cuando las personas interactúan con los ordenadores, hay mucha información que no se proporciona a propósito. Mediante el estudio de estas interacciones implícitas es posible entender qué características de la interfaz de usuario son beneficiosas (o no), derivando así en implicaciones para el diseño de futuros sistemas interactivos. La principal ventaja de aprovechar datos implícitos del usuario en aplicaciones informáticas es que cualquier interacción con el sistema puede contribuir a mejorar su utilidad. Además, dichos datos eliminan el coste de tener que interrumpir al usuario para que envíe información explícitamente sobre un tema que en principio no tiene por qué guardar relación con la intención de utilizar el sistema. Por el contrario, en ocasiones las interacciones implícitas no proporcionan datos claros y concretos. Por ello, hay que prestar especial atención a la manera de gestionar esta fuente de información. El propósito de esta investigación es doble: 1) aplicar una nueva visión tanto al diseño como al desarrollo de aplicaciones que puedan reaccionar consecuentemente a las interacciones implícitas del usuario, y 2) proporcionar una serie de metodologías para la evaluación de dichos sistemas interactivos. Cinco escenarios sirven para ilustrar la viabilidad y la adecuación del marco de trabajo de la tesis. Resultados empíricos con usuarios reales demuestran que aprovechar la interacción implícita es un medio tanto adecuado como conveniente para mejorar de múltiples maneras los sistemas interactivos.Leiva Torres, LA. (2012). Diverse Contributions to Implicit Human-Computer Interaction [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17803Palanci

Mnews: A Study of Multilingual News Search Interfaces

With the global expansion of the Internet and the World Wide Web, users are becoming increasingly diverse, particularly in terms of languages. In fact, the number of polyglot Web users across the globe has increased dramatically. However, even such multilingual users often continue to suffer from unbalanced and fragmented news information, as traditional news access systems seldom allow users to simultaneously search for and/or compare news in different languages, even though prior research results have shown that multilingual users make significant use of each of their languages when searching for information online. Relatively little human-centered research has been conducted to better understand and support multilingual user abilities and preferences. In particular, in the fields of cross-language and multilingual search, the majority of research has focused primarily on improving retrieval and translation accuracy, while paying comparably less attention to multilingual user interaction aspects. The research presented in this thesis provides the first large-scale investigations of multilingual news consumption and querying/search result selection behaviors, as well as a detailed comparative analysis of polyglots’ preferences and behaviors with respect to different multilingual news search interfaces on desktop and mobile platforms. Through a set of 4 phases of user studies, including surveys, interviews, as well as task-based user studies using crowdsourcing and laboratory experiments, this thesis presents the first human-centered studies in multilingual news access, aiming to drive the development of personalized multilingual news access systems to better support each individual user

Building and exploiting context on the web

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A Browser Extension Assisting Tabbed Browsing Behavior Research

This thesis is focused on the tabbed browsing behavior research with the assistance of a Chrome browser extension. A Chrome browser extension was designed and developed, aiming to better collect and arrange browsing behavioral data. This thesis put an emphasis on the engineering aspect of the extension. After the extension was developed, a lab study were carried out to validate the usability of the extension and to explore the relation between task difficulty and browsing behaviors. Results show that applying new metrics and hierarchical linear model improves the prediction performance for task difficulty. Results also report a few behavioral observations to further validate the outcomes of the lab study. These findings can potentially help design systems that better predict the task difficulty and provide assistance for users in case of browsing clutter

Online multitasking and user engagement

Users often access and re-access more than one site during an online session, effectively engaging in multitasking. In this paper, we study the effect of online multitasking on two widely used engagement metrics designed to capture users browsing behavior with a site. Our study is based on browsing data of 2.5M users across 760 sites encompass-ing diverse types of services such as social media, news and mail. To account for multitasking we need to redefine how user sessions are represented and we need to adapt the met-rics under study. We introduce a new representation of user sessions: tree-streams – as opposed to the commonly used click-streams – present a more accurate picture of the brows-ing behavior of a user that includes how users switch between sites (e.g., hyperlinking, teleporting, backpaging). We then discuss a number of insights on multitasking patterns, and show how these help to better understand how users engage with sites. Finally, we define metrics that characterize mul-titasking during online sessions and show how they provide additional insights to standard engagement metrics

Interest identification from browser tab titles: A systematic literature review

Modeling and understanding users interests has become an essential part of our daily lives. A variety of business processes and a growing number of companies employ various tools to such an end. The outcomes of these identification strategies are beneficial for both companies and users: the former are more likely to offer services to those customers who really need them, while the latter are more likely to get the service they desire. Several works have been carried out in the area of user interests identification. As a result, it might not be easy for researchers, developers, and users to orient themselves in the field; that is, to find the tools and methods that they most need, to identify ripe areas for further investigations, and to propose the development and adoption of new research plans. In this study, to overcome these potential shortcomings, we performed a systematic literature review on user interests identification. We used as input data browsing tab titles. Our goal here is to offer a service to the readership, which is capable of systematically guiding and reliably orienting researchers, developers, and users in this very vast domain. Our findings demonstrate that the majority of the research carried out in the field gathers data from either social networks (such as Twitter, Instagram and Facebook) or from search engines, leaving open the question of what to do when such data is not available

Study of result presentation and interaction for aggregated search

The World Wide Web has always attracted researchers and commercial search engine companies due to the enormous amount of information available on it. "Searching" on web has become an integral part of today's world, and many people rely on it when looking for information. The amount and the diversity of information available on the Web has also increased dramatically. Due to which, the researchers and the search engine companies are making constant efforts in order to make this information accessible to the people effectively. Not only there is an increase in the amount and diversity of information available online, users are now often seeking information on broader topics. Users seeking information on broad topics, gather information from various information sources (e.g, image, video, news, blog, etc). For such information requests, not only web results but results from different document genre and multimedia contents are also becoming relevant. For instance, users' looking for information on "Glasgow" might be interested in web results about Glasgow, Map of Glasgow, Images of Glasgow, News of Glasgow, and so on. Aggregated search aims to provide access to this diverse information in a unified manner by aggregating results from different information sources on a single result page. Hence making information gathering process easier for broad topics. This thesis aims to explore the aggregated search from the users' perspective. The thesis first and foremost focuses on understanding and describing the phenomena related to the users' search process in the context of the aggregated search. The goal is to participate in building theories and in understanding constraints, as well as providing insights into the interface design space. In building this understanding, the thesis focuses on the click-behavior, information need, source relevance, dynamics of search intents. The understanding comes partly from conducting users studies and, from analyzing search engine log data. While the thematic (or topical) relevance of documents is important, this thesis argues that the "source type" (source-orientation) may also be an important dimension in the relevance space for investigating in aggregated search. Therefore, relevance is multi-dimensional (topical and source-orientated) within the context of aggregated search. Results from the study suggest that the effect of the source-orientation was a significant factor in an aggregated search scenario. Hence adds another dimension to the relevance space within the aggregated search scenario. The thesis further presents an effective method which combines rule base and machine learning techniques to identify source-orientation behind a user query. Furthermore, after analyzing log-data from a search engine company and conducting user study experiments, several design issues that may arise with respect to the aggregated search interface are identified. In order to address these issues, suitable design guidelines that can be beneficial from the interface perspective are also suggested. To conclude, aim of this thesis is to explore the emerging aggregated search from users' perspective, since it is a very important for front-end technologies. An additional goal is to provide empirical evidence for influence of aggregated search on users searching behavior, and identify some of the key challenges of aggregated search. During this work several aspects of aggregated search will be uncovered. Furthermore, this thesis will provide a foundations for future research in aggregated search and will highlight the potential research directions

Veebi otsingumootorid ja vajadus keeruka informatsiooni järele

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Veebi otsingumootorid on muutunud põhiliseks teabe hankimise vahenditeks internetist. Koos otsingumootorite kasvava populaarsusega on nende kasutusala kasvanud lihtsailt päringuilt vajaduseni küllaltki keeruka informatsiooni otsingu järele. Samas on ka akadeemiline huvi otsingu vastu hakanud liikuma lihtpäringute analüüsilt märksa keerukamate tegevuste suunas, mis hõlmavad ka pikemaid ajaraame. Praegused otsinguvahendid ei toeta selliseid tegevusi niivõrd hästi nagu lihtpäringute juhtu. Eriti kehtib see toe osas koondada mitme päringu tulemusi kokku sünteesides erinevate lihtotsingute tulemusi ühte uude dokumenti. Selline lähenemine on alles algfaasis ja ning motiveerib uurijaid arendama vastavaid vahendeid toetamaks taolisi informatsiooniotsingu ülesandeid. Käesolevas dissertatsioonis esitatakse rida uurimistulemusi eesmärgiga muuta keeruliste otsingute tuge paremaks kasutades tänapäevaseid otsingumootoreid. Alameesmärkideks olid: (a) arendada välja keeruliste otsingute mudel, (b) mõõdikute loomine kompleksotsingute mudelile, (c) eristada kompleksotsingu ülesandeid lihtotsingutest ning teha kindlaks, kas neid on võimalik mõõta leides ühtlasi lihtsaid mõõdikuid kirjeldamaks nende keerukust, (d) analüüsida, kui erinevalt kasutajad käituvad sooritades keerukaid otsinguülesandeid kasutades veebi otsingumootoreid, (e) uurida korrelatsiooni inimeste tava-veebikasutustavade ja nende otsingutulemuslikkuse vahel, (f) kuidas inimestel läheb eelhinnates otsinguülesande raskusastet ja vajaminevat jõupingutust ning (g) milline on soo ja vanuse mõju otsingu tulemuslikkusele. Keeruka veebiotsingu ülesanded jaotatakse edukalt kolmeastmeliseks protsessiks. Esitatakse sellise protsessi mudel; seda protsessi on ühtlasi võimalik ka mõõta. Edasi näidatakse kompleksotsingu loomupäraseid omadusi, mis teevad selle eristatavaks lihtsamatest juhtudest ning näidatakse ära katsemeetod sooritamaks kompleksotsingu kasutaja-uuringuid. Demonstreeritakse põhilisi samme raamistiku “Search-Logger” (eelmainitud metodoloogia tehnilise teostuse) rakendamisel kasutaja-uuringutes. Esitatakse sellisel viisil teostatud uuringute tulemused. Lõpuks esitatakse ATMS meetodi realisatsioon ja rakendamine parandamaks kompleksotsingu vajaduste tuge kaasaegsetes otsingumootorites.Search engines have become the means for searching information on the Internet. Along with the increasing popularity of these search tools, the areas of their application have grown from simple look-up to rather complex information needs. Also the academic interest in search has started to shift from analyzing simple query and response patterns to examining more sophisticated activities covering longer time spans. Current search tools do not support those activities as well as they do in the case of simple look-up tasks. Especially the support for aggregating search results from multiple search-queries, taking into account discoveries made and synthesizing them into a newly compiled document is only at the beginning and motivates researchers to develop new tools for supporting those information seeking tasks. In this dissertation I present the results of empirical research with the focus on evaluating search engines and developing a theoretical model of the complex search process that can be used to better support this special kind of search with existing search tools. It is not the goal of the thesis to implement a new search technology. Therefore performance benchmarks against established systems such as question answering systems are not part of this thesis. I present a model that decomposes complex Web search tasks into a measurable, three-step process. I show the innate characteristics of complex search tasks that make them distinguishable from their less complex counterparts and showcase an experimentation method to carry out complex search related user studies. I demonstrate the main steps taken during the development and implementation of the Search-Logger study framework (the technical manifestation of the aforementioned method) to carry our search user studies. I present the results of user studies carried out with this approach. Finally I present development and application of the ATMS (awareness-task-monitor-share) model to improve the support for complex search needs in current Web search engines