@article{yuan_singh_murukannaiah_2021, title={An interpretable framework for investigating the neighborhood effect in POI recommendation}, volume={16}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0255685}, abstractNote={Geographical characteristics have been proven to be effective in improving the quality of point-of-interest (POI) recommendation. However, existing works on POI recommendation focus on cost (time or money) of travel for a user. An important geographical aspect that has not been studied adequately is theneighborhood effect, which captures a user’s POI visiting behavior based on the user’s preference not only to a POI, but also to the POI’s neighborhood. To provide an interpretable framework to fully study the neighborhood effect, first, we develop different sets of insightful features, representing different aspects of neighborhood effect. We employ a Yelp data set to evaluate how different aspects of the neighborhood effect affect a user’s POI visiting behavior. Second, we propose a deep learning–based recommendation framework that exploits the neighborhood effect. Experimental results show that our approach is more effective than two state-of-the-art matrix factorization–based POI recommendation techniques.}, number={8}, journal={PLOS ONE}, author={Yuan, Guangchao and Singh, Munindar P. and Murukannaiah, Pradeep K.}, year={2021}, month={Aug} }
 @article{ajmeri_murukannaiah_singh_2020, title={Ethics in Self-* Sociotechnical Systems (Tutorial Abstract)}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85092729693&partnerID=MN8TOARS}, DOI={10.1109/ACSOS-C51401.2020.00070}, abstractNote={The surprising capabilities demonstrated by AI technologies overlaid on detailed data and fine-grained control give cause for concern that agents can wield enormous power over human welfare, drawing increasing attention to ethics in AI.}, journal={2020 IEEE INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING AND SELF-ORGANIZING SYSTEMS COMPANION (ACSOS-C 2020)}, publisher={IEEE}, author={Ajmeri, Nirav and Murukannaiah, Pradeep K. and Singh, Munindar P.}, year={2020}, pages={249–249} }
 @article{murukannaiah_singh_2020, title={From Machine Ethics to Internet Ethics: Broadening the Horizon}, volume={24}, ISSN={["1941-0131"]}, DOI={10.1109/MIC.2020.2989935}, abstractNote={This article introduces some of the key concepts and challenges pertaining to ethics from the standpoint of Internet applications.}, number={3}, journal={IEEE INTERNET COMPUTING}, author={Murukannaiah, Pradeep K. and Singh, Munindar P.}, year={2020}, pages={51–57} }
 @article{fogues_murukannaiah_such_singh_2017, title={Sharing Policies in Multiuser Privacy Scenarios: Incorporating Context, Preferences, and Arguments in Decision Making}, volume={24}, ISSN={["1557-7325"]}, url={https://publons.com/publon/21294367/}, DOI={10.1145/3038920}, abstractNote={Social network services (SNSs) enable users to conveniently share personal information. Often, the information shared concerns other people, especially other members of the SNS. In such situations, two or more people can have conflicting privacy preferences; thus, an appropriate sharing policy may not be apparent. We identify such situations asmultiuser privacy scenarios. Current approaches propose finding a sharing policy through preference aggregation. However, studies suggest that users feel more confident in their decisions regarding sharing when they know the reasons behind each other’s preferences. The goals of this paper are (1) understanding how people decide the appropriate sharing policy in multiuser scenarios where arguments are employed, and (2) developing a computational model to predict an appropriate sharing policy for a given scenario. We report on a study that involved a survey of 988 Amazon Mechanical Turk (MTurk) users about a variety of multiuser scenarios and the optimal sharing policy for each scenario. Our evaluation of the participants’ responses reveals that contextual factors, user preferences, and arguments influence the optimal sharing policy in a multiuser scenario. We develop and evaluate an inference model that predicts the optimal sharing policy given the three types of features. We analyze the predictions of our inference model to uncover potential scenario types that lead to incorrect predictions, and to enhance our understanding of when multiuser scenarios are more or less prone to dispute.}, number={1}, journal={ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION}, author={Fogues, Ricard L. and Murukannaiah, Pradeep K. and Such, Jose M. and Singh, Munindar P.}, year={2017}, month={Mar} }
 @article{murukannaiah_ajmeri_singh_2016, place={United States}, title={Acquiring Creative Requirements from the Crowd Understanding the Influences of Personality and Creative Potential in Crowd RE}, ISSN={["2332-6441"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85007232627&partnerID=MN8TOARS}, DOI={10.1109/re.2016.68}, abstractNote={As a creative discipline, Requirements Engineering (RE), lends importance to understanding the associated human factors. Crowd RE, the approach of acquiring requirements from members of the public-the so-called crowd-emphasizes human factors further. We investigate how human personality and creative potential influence a requirement acquisition task. These factors are of specific importance to Crowd RE because (1) crowd workers are generally not trained in RE, and (2) a key motivation in engaging them is to benefit from their creativity. We propose a sequential Crowd RE process, where workers in one stage review requirements from the previous stage and produce additional requirements. To reduce potential information overload in this process, we propose strategies for selecting requirements from one stage to expose to workers in later stages. We conducted a study on Amazon Mechanical Turk tasking 300 workers with creating requirements via the above sequential process (in the domain of smart home applications for concreteness) and tasking an additional 300 workers to rate the creativity (novelty and usefulness) of those requirements. Our findings offer insights on how to carry out Crowd RE effectively. First, we find that a crowd worker's (1) creative potential, and personality traits of openness and conscientiousness have significant positive influence on the novelty of the worker's ideas, and (2) personality traits of agreeableness and conscientiousness have significant positive influence, but extraversion has significant negative influence on the usefulness of the worker's ideas. Second, we find that exposing a worker to ideas from previous workers cognitively stimulates the worker to produce creative ideas. Third, we identify effective strategies based on personality traits and creative potential for selecting a few requirements from a pool of previous requirements to stimulate a worker.}, journal={2016 IEEE 24TH INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE (RE)}, publisher={IEEE}, author={Murukannaiah, Pradeep K. and Ajmeri, Nirav and Singh, Munindar P.}, year={2016}, pages={176–185} }
 @article{murukannaiah_ajmeri_singh_2016, title={Engineering Privacy in Social Applications}, volume={20}, ISSN={["1941-0131"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84963904023&partnerID=MN8TOARS}, DOI={10.1109/mic.2016.30}, abstractNote={Experience with a social application depends crucially upon how it supports or interferes with the users' social expectations. Because privacy is central to the user's experience, the authors introduce Danio, a methodology based on modeling users' expectations in various contexts. Preliminary evaluation involving 34 developers suggests that Danio simplifies the development of social applications and saves time during implementation and testing.}, number={2}, journal={IEEE INTERNET COMPUTING}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Murukannaiah, Pradeep K. and Ajmeri, Nirav and Singh, Munindar P.}, year={2016}, pages={72–76} }
 @article{yuan_murukannaiah_singh_2016, title={Percimo: A Personalized Community Model for Location Estimation in Social Media}, url={https://publons.com/publon/21294383/}, DOI={10.1109/asonam.2016.7752245}, abstractNote={User location is crucial in understanding the dynamics of user activities, especially in relating their online and offline aspects. However, users' social media activities, such as tweets sent, do not always reveal their location. We consider the problem of estimating geo-tags for tweets and develop a comprehensive approach that incorporates textual content, the user's personalized behavior, and the user's social relationships. Our approach, Percimo, considers the two major kinds of communal attachment, which have distinct computational ramifications. We evaluate Percimo via three geo-social graphs based on the mutual-follow relationships of Twitter users, their geographical distance (computed from their geotagged tweets), and their preferences for location categories (collected from Foursquare). We find that Percimo yields a smaller prediction error than the two state-of-the-art approaches we compare with.}, journal={PROCEEDINGS OF THE IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING ASONAM}, author={Yuan, G. C. and Murukannaiah, P. K. and Singh, Munindar P.}, year={2016}, pages={271–278} }
 @article{murukannaiah_singh_2015, title={Platys: An Active Learning Framework for Place-Aware Application Development and Its Evaluation}, volume={24}, ISSN={["1557-7392"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84930154899&partnerID=MN8TOARS}, DOI={10.1145/2729976}, abstractNote={
            We introduce a high-level abstraction of location called
            place
            . A place derives its meaning from a user's physical space, activities, or social context. In this manner, place can facilitate improved user experience compared to the traditional representation of location, which is spatial coordinates. We propose the
            Platys
            framework as a way to address the special challenges of place-aware application development. The core of Platys is a middleware that (1) learns a model of places specific to each user via
            active learning
            , a machine learning paradigm that seeks to reduce the user-effort required for training the middleware, and (2) exposes the learned user-specific model of places to applications at run time, insulating application developers from dealing with both low-level sensors and user idiosyncrasies in perceiving places.
          }, number={3}, journal={ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY}, author={Murukannaiah, Pradeep K. and Singh, Munindar P.}, year={2015}, month={May} }
 @article{zavala_murukannaiah_poosamani_finin_joshi_rhee_singh_2015, title={Platys: From Position to Place-Oriented Mobile Computing}, volume={36}, ISSN={["0738-4602"]}, url={https://publons.com/publon/21294393/}, DOI={10.1609/aimag.v36i2.2584}, abstractNote={The Platys project focuses on developing a high‐level, semantic notion of location called place. A place, unlike a geospatial position, derives its meaning from a user's actions and interactions in addition to the physical location where it occurs. Our aim is to enable the construction of a large variety of applications that take advantage of place to render relevant content and functionality and, thus, improve user experience. We consider elements of context that are particularly related to mobile computing. The main problems we have addressed to realize our place‐oriented mobile computing vision are representing places, recognizing places, and engineering place‐aware applications. We describe the approaches we have developed for addressing these problems and related subproblems. A key element of our work is the use of collaborative information sharing where users' devices share and integrate knowledge about places. Our place ontology facilitates such collaboration. Declarative privacy policies allow users to specify contextual features under which they prefer to share or not share their information.}, number={2}, journal={AI MAGAZINE}, author={Zavala, Laura and Murukannaiah, Pradeep K. and Poosamani, Nithyananthan and Finin, Tim and Joshi, Anupam and Rhee, Injong and Singh, Munindar P.}, year={2015}, pages={50–62} }
 @article{murukannaiah_kalia_telang_singh_2015, title={Resolving Goal Conflicts via Argumentation-Based Analysis of Competing Hypotheses}, url={https://publons.com/publon/21294399/}, DOI={10.1109/re.2015.7320418}, abstractNote={A stakeholder's beliefs influence his or her goals. However, a stakeholder's beliefs may not be consistent with the goals of all stakeholders of a system being constructed. Such belief-goal inconsistencies could manifest themselves as conflicting goals of the system to be. We propose Arg-ACH, a novel approach for capturing inconsistencies between stakeholders' goals and beliefs, and resolving goal conflicts. Arg-ACH employs a hybrid of (1) the analysis of competing hypotheses (ACH), a structured analytic technique, for systematically eliciting stakeholders' goals and beliefs, and (2) rational argumentation for determining belief-goal inconsistencies to resolve conflicts. Arg-ACH treats conflicting goals as hypotheses that compete with each other and the winning hypothesis as a goal of the system to be. Arg-ACH systematically captures the trail of a requirements engineer's thought process in resolving conflicts. We evaluated Arg-ACH via a study in which 20 subjects applied Arg-ACH or ACH to resolve goal conflicts in a sociotechnical system concerning national security. We found that Arg-ACH is superior to ACH with respect to completeness and coverage of belief search; length of belief chaining; ease of use; explicitness of the assumptions made; and repeatability of conclusions across subjects. Not surprisingly, Arg-ACH required more time than ACH: although this is justified by improvements in quality, the gap could be reduced through better tooling.}, journal={IEEE 25TH INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE (RE)}, author={Murukannaiah, P. K. and Kalia, A. K. and Telang, P. R. and Singh, Munindar P.}, year={2015}, pages={156–165} }
 @inproceedings{kalia_murukannaiah_singh_2015, title={TRACE: A dynamic model of trust for people-driven service engagements combining trust with risk, commitments, and emotions}, volume={9435}, booktitle={Service-oriented computing, (icsoc 2015)}, author={Kalia, A. K. and Murukannaiah, P. K. and Singh, M. P.}, year={2015}, pages={353–361} }
 @article{murukannaiah_singh_2014, title={Understanding Location-Based User Experience}, volume={18}, ISSN={["1941-0131"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84908507901&partnerID=MN8TOARS}, DOI={10.1109/mic.2014.127}, abstractNote={As location-based applications increase in scope and variety, engineering them to deliver a high-quality user experience becomes increasingly important. The authors describe how user experience criteria map to location-based applications, the special demands these criteria place on modeling, and how to realize such applications to obtain high-quality user experience.}, number={6}, journal={IEEE INTERNET COMPUTING}, author={Murukannaiah, Pradeep K. and Singh, Munindar P.}, year={2014}, pages={72–76} }
 @article{murukannaiah_singh_2012, title={Platys Social: Relating Shared Places and Private Social Circles}, volume={16}, ISSN={["1941-0131"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84858220653&partnerID=MN8TOARS}, DOI={10.1109/mic.2011.106}, abstractNote={Social circles can be valuable in online applications, but existing approaches don't readily support such grouping: they either require a user to manually tag connections or offer no more than broad-brush acquaintanceship between connections. Platys Social is a novel approach that learns users' social circles and prioritizes their connections by bringing together contextual information and user interactions. Platys Social runs incrementally, can execute on a resource-limited mobile device, and can potentially avoid storing users' private information on a remote site.}, number={3}, journal={IEEE INTERNET COMPUTING}, author={Murukannaiah, Pradeep K. and Singh, Munindar P.}, year={2012}, pages={53–59} }