Information retrieval systems often consider search-session and immediately preceding web-browsing history as the context for predicting users’ present information needs. However, such is only available when a user’s needs originate from web or users have issued queries in search session. Here, we study effect of more extensive recorded everyday digital activities by monitoring all interacted with communicated using personal computers. Twenty individuals were recruited 14 days 24/7...

Understanding users' search behavior has largely relied on the information available from engine logs, which provide limited about contextual factors affecting behavior. Consequently, questions such as how intentions, task goals, and substances of tasks affect behavior, well what triggers needs, remain unanswered. We report an experiment in naturalistic was captured by analyzing 24/7 continuous recordings participants' computer screens. Written diaries describing were collected used...

Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services operating systems. Previous research often focuses on specific recommendation with data captured from interactions an individual application. The quality of recommendations also evaluated addressing only computational measures accuracy, without investigating the usefulness realistic tasks. aim this work to synthesize area...

We investigate to what extent it is possible infer a user’s work tasks by digital activity monitoring and use the task models for proactive information retrieval. Ten participants volunteered study, in which their computer screen was monitored related logs were recorded 14 days. Corresponding diary entries collected provide ground truth detection method. report two experiments using this data. The unsupervised experiment conducted detect topic modeling. results show an average accuracy of...

Web searches often originate from conversations in which people engage before they perform a search. Therefore, can be valuable source of context with to support the search process. We investigate whether spoken input used as improve query auto-completion. model temporal dynamics conversational preceding queries and use these models re-rank auto-completion suggestions. Data were collected controlled experiment comprised among 12 participant pairs conversing about movies or traveling. Search...

We demonstrate proactive information retrieval via screen surveillance. A user's digital activities are continuously monitored by capturing all content on a using optical character recognition. This includes applications and services being exploited relies each individual computer usage, such as their Web browsing, emails, instant messaging, word processing. Topic modeling is then applied to detect the topical activity context retrieve information. system that proactively retrieves from...

We study the effect of contextual information obtained from a user’s digital trace on Web search performance. Contextual is modeled using Dirichlet–Hawkes processes (DHP) and used in augmenting queries. The context captured by monitoring all naturally occurring user behavior continuous 24/7 recordings screen associating with queries issued users. report field which 13 participants installed recording activity system their laptops for 14 days, resulting data associated data. A query...

Individuals are known to differ in cognitive abilities, affecting their behavior and information processing digital environments. However, we have a limited understanding of which behaviors affected, how, whether some features extracted from can predict abilities. Consequently, researchers may miss opportunities design support individuals with personalized experiences detect those who benefit additional interventions. To characterize behaviors, collected 24/7 screen recordings, input...

Abstract Differences in cognitive abilities affect search behaviors, but this has mostly been observed laboratory experiments. There is limited research on how users for information real‐world, naturalistic settings and real‐world behaviors relate to abilities. In study, we investigated a wide range of behavioral data captured from real‐life tasks, their association with users' abilities, the potential automatically inferring these data. Furthermore, aimed determine quantity monitoring...

Our digital life consists of activities that are organized around tasks and exhibit different user states in the contexts these activities. Previous works have shown activity monitoring can be used to predict entities users will need perform tasks. There been methods developed automatically detect a user. However, studies typically support only specific applications tasks, relatively little research has conducted on real-life This article introduces state modeling prediction with contextual...

Exploratory search starts with ill-defined goals and involves browsing, learning, formulating new targets for search. To fluidly support such dynamic behaviours, we focus on devising interactive visual facets (IVF), visualising information to user comprehension control of the space. do this, reviewed existing faceted interfaces derived two design requirements (DR) that have not been fully addressed fluid interactions in exploratory We then exemplified through an IVF tool, which coordinates a...

Our everyday digital tasks require access to information from a wide range of applications and systems. Although traditional search systems can help find information, they usually operate within one application (e.g., email client or web browser) the user's cognitive effort attention formulate proper queries. In this paper, we demonstrate EntityBot, system that proactively provides useful supporting entities across boundaries without requiring explicit query formulation. methodology is...

Everyday digital tasks can highly benefit from systems that recommend the right information to use at time. However, existing solutions typically support only specific applications and tasks. In this demo, we showcase EntityBot, a system captures context across application boundaries recommends entities related current task. The user's activity is continuously monitored by capturing all content on computer screen using optical character recognition. This includes services being used...

We present the design and implementation of mailVis, an interactive visual interface for email boxes that facilitates re-finding emails. Email tasks can be challenging, involving scanning many emails modifying query as search progresses. designed mailVis such in which user would benefit from having memory clues multiple options to direct search. During process, we devised a novel interaction technique, filter swipe, combines filtering selection into one action rapidly skimming individual...

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The impact of users’ age on real-world search behavior remains relatively understudied, despite the recognized variations in information among individuals controlled laboratory studies. This paper presents two user studies aimed at addressing this knowledge gap. first study examines within context simulated tasks, while second investigates tasks derived from natural computer interactions. Data comprising and interaction logs recorded twenty participants, ranging 19 to 71 years, were analyzed...

Despite the growth of personal digital information use, both in scale and application diversity, conventional user models are still reliant on limited input data to improve a variety services for specific applications tasks. This trend toward increased diversity renders it difficult system generate inferences about user's evolving interests naturalistic tasks real-life settings. workshop paper introduces novel approach, aimed at training model recognize basis behavioral via continuous screen...

Abstract Exploratory search starts with ill-defined goals and involves browsing, learning, formulating new targets for search. To fluidly support such dynamic behaviours, we focus on devising interactive visual facets (IVF) , visualising information to user comprehension control of the space. We reviewed existing faceted interfaces derived two design requirements (DR) that have not been fully addressed fluid interactions in exploratory then exemplified through an IVF tool, which coordinates...

One of the primary purposes visualization is to assist users in discovering insights. While there has been much research information aiming at complex data transformation and novel presentation techniques, relatively little done understand how derive insights through interactive data. This paper presents a crowdsourced study with 158 participants investigating relation between entity-based interaction (an action + its target entity) resulting insight. To this end, we generalized an existing...

Exploratory search starts with ill-defined goals and involves browsing, learning, formulating new targets for search. To fluidly support such dynamic behaviours, we focus on devising interactive visual facets (IVF), visualising information to user comprehension control of the space. do this, reviewed existing faceted interfaces derived two design requirements (DR) that have not been fully addressed fluid interactions in exploratory We then exemplified through an IVF tool, which coordinates a...