Smart City Development with Urban Transfer Learning

Nowadays, the smart city development levels of different cities are still unbalanced. For a large number of cities which just started development, the governments will face a critical cold-start problem: 'how to develop a new smart city service with limited data?'. To address this problem, transfer learning can be leveraged to accelerate the smart city development, which we term the urban transfer learning paradigm. This article investigates the common process of urban transfer learning, aiming to provide city planners and relevant practitioners with guidelines on how to apply this novel learning paradigm. Our guidelines include common transfer strategies to take, general steps to follow, and case studies in public safety, transportation management, etc. We also summarize a few research opportunities and expect this article can attract more researchers to study urban transfer learning

On the Anonymization of Differentially Private Location Obfuscation

Obfuscation techniques in location-based services (LBSs) have been shown useful to hide the concrete locations of service users, whereas they do not necessarily provide the anonymity. We quantify the anonymity of the location data obfuscated by the planar Laplacian mechanism and that by the optimal geo-indistinguishable mechanism of Bordenabe et al. We empirically show that the latter provides stronger anonymity than the former in the sense that more users in the database satisfy k-anonymity. To formalize and analyze such approximate anonymity we introduce the notion of asymptotic anonymity. Then we show that the location data obfuscated by the optimal geo-indistinguishable mechanism can be anonymized by removing a smaller number of users from the database. Furthermore, we demonstrate that the optimal geo-indistinguishable mechanism has better utility both for users and for data analysts.Comment: ISITA'18 conference pape

Anticipating Information Needs Based on Check-in Activity

In this work we address the development of a smart personal assistant that is capable of anticipating a user's information needs based on a novel type of context: the person's activity inferred from her check-in records on a location-based social network. Our main contribution is a method that translates a check-in activity into an information need, which is in turn addressed with an appropriate information card. This task is challenging because of the large number of possible activities and related information needs, which need to be addressed in a mobile dashboard that is limited in size. Our approach considers each possible activity that might follow after the last (and already finished) activity, and selects the top information cards such that they maximize the likelihood of satisfying the user's information needs for all possible future scenarios. The proposed models also incorporate knowledge about the temporal dynamics of information needs. Using a combination of historical check-in data and manual assessments collected via crowdsourcing, we show experimentally the effectiveness of our approach.Comment: Proceedings of the 10th ACM International Conference on Web Search and Data Mining (WSDM '17), 201

CULTURAL MAPPING SEKOLAH MENENGAH KEJURUAN DAN INDUSTRI BATIK DI INDONESIA

Sekolah Menengah Kejuruan (SMK) dan industri diharapkan saling bekerjasama untuk meningkatkan lulusan SMK dan mengembangkan industri salah satunya bidang keahlian batik. Peneliti ini di latar belakangi oleh pentingnya partnership antara SMK dan industri dalam upaya memetakan potensi masing-masing lembaga untuk tercapainya sinergisitas. Tujuan penelitian ini adalah melakukan cultural mapping SMK keahlian batik dan industri batik di Indonesia yang meliputi mapping SMK program keahlian batik, industri batik, dan cultural mapping SMK dan industri batik dengan pendekatan metode penelitian yang menggunakan analisis website SMK keahlian batik dan industri batik. Dibantu oleh software @Geomash-Microsoft yang digunakan olah data pada Microsoft Excel. Temuan penelitian mengenai profil SMK dengan jumlah keseluruhan di Indonesia, dengan pendekatan relevansi dimensi diantaranya dimensi kualitas banyaknya SMK keahlian batik di Indonesia bekerjasama dengan industri batik dapat membuat lulusan SMK semakin bertambah sebab mitra berpengaruh terhadap hasil lulusan siswa di SMK, dimensi kuantitas dengan banyaknya jumlah industri batik di suatu provinsi menguntungkan bagi siswa untuk melaksanakan praktek di industri dan industri juga dapat meamnfaatkan lulusan SMK, dimensi lokasi terkait dengan wilayah industri yang memerlukan pasokan tenaga kerja sesuai dengan kebutuhan industri, dan dimensi waktu perkembangan pendidikan dan industri masa kini hingga masa depan. Jumlah SMK keahlian batik dan industri batik terbanyak berada di Pulau Jawa, yang diketahui jawa merupakan tempat batik berasal. Penelitian ini mengenai cultural mapping sekolah menengah kejuruan dan indsutri batik di Indonesia bertujuan untuk dapat memvisualisasikan perbandingan antara jumlah SMK keahlian batik dengan jumlah industri batik di Indonesia

Local Distribution Obfuscation via Probability Coupling

We introduce a general model for the local obfuscation of probability distributions by probabilistic perturbation, e.g., by adding differentially private noise, and investigate its theoretical properties. Specifically, we relax a notion of distribution privacy (DistP) by generalizing it to divergence, and propose local obfuscation mechanisms that provide divergence distribution privacy. To provide f-divergence distribution privacy, we prove that probabilistic perturbation noise should be added proportionally to the Earth mover's distance between the probability distributions that we want to make indistinguishable. Furthermore, we introduce a local obfuscation mechanism, which we call a coupling mechanism, that provides divergence distribution privacy while optimizing the utility of obfuscated data by using exact/approximate auxiliary information on the input distributions we want to protect.Comment: Full version of Allerton 2019 paper (This paper extends some part of the unpublished v3 of arXiv:1812.00939, while v4 of arXiv:1812.00939 extends the other part and is published in ESORICS'19.