Recommendation, collaboration and social search

This chapter considers the social component of interactive information retrieval: what is the role of other people in searching and browsing? For simplicity we begin by considering situations without computers. After all, you can interactively retrieve information without a computer; you just have to interact with someone or something else. Such an analysis can then help us think about the new forms of collaborative interactions that extend our conceptions of information search, made possible by the growth of networked ubiquitous computing technology. Information searching and browsing have often been conceptualized as a solitary activity, however they always have a social component. We may talk about 'the' searcher or 'the' user of a database or information resource. Our focus may be on individual uses and our research may look at individual users. Our experiments may be designed to observe the behaviors of individual subjects. Our models and theories derived from our empirical analyses may focus substantially or exclusively on an individual's evolving goals, thoughts, beliefs, emotions and actions. Nevertheless there are always social aspects of information seeking and use present, both implicitly and explicitly. We start by summarizing some of the history of information access with an emphasis on social and collaborative interactions. Then we look at the nature of recommendations, social search and interfaces to support collaboration between information seekers. Following this we consider how the design of interactive information systems is influenced by their social elements

The other side of the social web: A taxonomy for social information access

The power of the modern Web, which is frequently called the Social Web or Web 2.0, is frequently traced to the power of users as contributors of various kinds of contents through Wikis, blogs, and resource sharing sites. However, the community power impacts not only the production of Web content, but also the access to all kinds of Web content. A number of research groups worldwide explore what we call social information access techniques that help users get to the right information using "collective wisdom" distilled from actions of those who worked with this information earlier. This invited talk offers a brief introduction into this important research stream and reviews recent works on social information access performed at the University of Pittsburgh's PAWS Lab lead by the author. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM)

Intent-Aware Contextual Recommendation System

Recommender systems take inputs from user history, use an internal ranking algorithm to generate results and possibly optimize this ranking based on feedback. However, often the recommender system is unaware of the actual intent of the user and simply provides recommendations dynamically without properly understanding the thought process of the user. An intelligent recommender system is not only useful for the user but also for businesses which want to learn the tendencies of their users. Finding out tendencies or intents of a user is a difficult problem to solve. Keeping this in mind, we sought out to create an intelligent system which will keep track of the user's activity on a web-application as well as determine the intent of the user in each session. We devised a way to encode the user's activity through the sessions. Then, we have represented the information seen by the user in a high dimensional format which is reduced to lower dimensions using tensor factorization techniques. The aspect of intent awareness (or scoring) is dealt with at this stage. Finally, combining the user activity data with the contextual information gives the recommendation score. The final recommendations are then ranked using filtering and collaborative recommendation techniques to show the top-k recommendations to the user. A provision for feedback is also envisioned in the current system which informs the model to update the various weights in the recommender system. Our overall model aims to combine both frequency-based and context-based recommendation systems and quantify the intent of a user to provide better recommendations. We ran experiments on real-world timestamped user activity data, in the setting of recommending reports to the users of a business analytics tool and the results are better than the baselines. We also tuned certain aspects of our model to arrive at optimized results.Comment: Presented at the 5th International Workshop on Data Science and Big Data Analytics (DSBDA), 17th IEEE International Conference on Data Mining (ICDM) 2017; 8 pages; 4 figures; Due to the limitation "The abstract field cannot be longer than 1,920 characters," the abstract appearing here is slightly shorter than the one in the PDF fil

Social Navigation of Food Recipes

The term Social Navigation captures every-day behaviour used to find information, people, and places – namely through watching, following, and talking to people. We discuss how to design information spaces to allow for social navigation. We applied our ideas in a recipe recommendation system. In a follow-up user study, subjects state that social navigation adds value to the service: it provides for social affordance, and it helps turning a space into a social place. The study also reveals some unresolved design issues, such as the snowball effect where more and more users follow each other down the wrong path, and privacy issues

GeoNotes: A Location-based Information System for Public Spaces

The basic idea behind location-based information systems is to connect information pieces to positions in outdoor or indoor space. Through position technologies such as Global Positioning System (GPS), GSM positioning, Wireless LAN positioning o

Enhancing the Digital Backchannel Backstage on the Basis of a Formative User Study

Contemporary higher education with its large audiences suffers from passivity of students. Enhancing the classroom with a digital backchannel can contribute to establishing and fostering active participation of and collaboration among students in the lecture. Therefore, we conceived the digital backchannel Backstage specifically tailored for the use in large classes. At an early phase of development we tested its core functionalities in a small-scale user study. The aim of the study was to gain first impressions of its adoption, and also to form a basis for further steps in the conception of Backstage. Regarding adoption we particularly focused on how Backstage influences the participants' questioning behavior, a salient aspect in learning. We observed that during the study much more questions were uttered on Backstage than being asked without backchannel support. Regarding the further development of Backstage we capitalized on the participants' usability feedback. The key of the refinement is the integration of presentation slides in Backstage, which leads to an interesting reconsideration of the user interactions of Backstage

Social Navigation in a Location-Based Information System

Much of contextaware application research has dealt with the technical aspects of context capturing and how to interpret the context of a user. Little effort has been spent on the experience and usage of these systems. This thesis will present the general aspects of social awareness and present an example on how these concepts can be implemented into a location-based information system to help users navigate a potential information overload. This thesis also states that giving the users an experience of not being alone in the system increases the pleasure of using such a system. However this implies a decrease in privacy. To demonstrate these ideas I will describe a locationbased information system, GeoNotes, built by a group of researchers at SICS, the Swedish Institute of Computer Science. I will state a set of interaction requirements for how to extend the GeoNotes system with functionality for social awareness. Furthermore I will set up functional requirements for those interaction requirements to after implementation be able to conclude which interaction requirements I have been able to implement for. I will also give suggestions on how to position users in a WLAN. The deliverable from this project is a locationbased information system with functionality for social awareness. However, it was not within this project to test the system on true users. Therefore the statement that this functionality can help users to navigate a potential information overload is still just a hypothesis. To retrieve the position of a user in a W-LAN a packet is sent to all base stations in the network. In the first returning packet the mac address of contacting base station is extracted. Each base station is therefore a unique position. Triangulation was discarded due to its sensitivity to noise and weather circumstances, although a system that uses triangulation would have offered a much higher granularity

A corpus-based analysis of route instructions in human-robot interaction

This paper investigates how users employ spatial descriptions to navigate a speech-enabled robot. We created a simulated environment in which users gave route instructions in a dialogic real-time interaction with a robot, which was operated by naïve participants. The ability of robot monitoring was also manipulated in two experimental conditions. The results provide evidence that the content of the instructions and strategies of the users vary depending on the conditions and demands of the interaction. As expected, the route instructions frequently were underspecified and arbitrary. The findings of this study elucidate the complexity in interpreting spatial language in HRI. However, they also point to the need for endowing mobile robots with richer dialogue resources to compensate for the uncertainties arising from language as well as the environment