6,031 research outputs found
Estimating Socioeconomic Status via Temporal-Spatial Mobility Analysis -- A Case Study of Smart Card Data
The notion of socioeconomic status (SES) of a person or family reflects the
corresponding entity's social and economic rank in society. Such information
may help applications like bank loaning decisions and provide measurable inputs
for related studies like social stratification, social welfare and business
planning. Traditionally, estimating SES for a large population is performed by
national statistical institutes through a large number of household interviews,
which is highly expensive and time-consuming. Recently researchers try to
estimate SES from data sources like mobile phone call records and online social
network platforms, which is much cheaper and faster. Instead of relying on
these data about users' cyberspace behaviors, various alternative data sources
on real-world users' behavior such as mobility may offer new insights for SES
estimation. In this paper, we leverage Smart Card Data (SCD) for public
transport systems which records the temporal and spatial mobility behavior of a
large population of users. More specifically, we develop S2S, a deep learning
based approach for estimating people's SES based on their SCD. Essentially, S2S
models two types of SES-related features, namely the temporal-sequential
feature and general statistical feature, and leverages deep learning for SES
estimation. We evaluate our approach in an actual dataset, Shanghai SCD, which
involves millions of users. The proposed model clearly outperforms several
state-of-art methods in terms of various evaluation metrics.Comment: 9 pages, double column, IEEE ICCCN 201
Privacy in the Smart City - Applications, Technologies, Challenges and Solutions
Many modern cities strive to integrate information technology into every aspect of city life to create so-called smart cities. Smart cities rely on a large number of application areas and technologies to realize complex interactions between citizens, third parties, and city departments. This overwhelming complexity is one reason why holistic privacy protection only rarely enters the picture. A lack of privacy can result in discrimination and social sorting, creating a fundamentally unequal society. To prevent this, we believe that a better understanding of smart cities and their privacy implications is needed. We therefore systematize the application areas, enabling technologies, privacy types, attackers and data sources for the attacks, giving structure to the fuzzy term “smart city”. Based on our taxonomies, we describe existing privacy-enhancing technologies, review the state of the art in real cities around the world, and discuss promising future research directions. Our survey can serve as a reference guide, contributing to the development of privacy-friendly smart cities
Mobile Information Retrieval
Mobile Information Retrieval (Mobile IR) is a relatively recent branch of
Information Retrieval (IR) that is concerned with enabling users to carry out,
using a mobile device, all the classical IR operations that they were used to
carry out on a desktop. This includes finding content available on local
repositories or on the web in response to a user query, interacting with the
system in an explicit or implicit way, reformulate the query and/or visualise
the content of the retrieved documents, as well as providing relevance
judgments to improve the retrieval process.
This book is structured as follows. Chapter 2 provides a very brief overview
of IR and of Mobile IR, briefly outlining what in Mobile IR is different from
IR. Chapter 3 provides the foundations of Mobile IR, looking at the
characteristics of mobile devices and what they bring to IR, but also looking
at how the concept of relevance changed from standard IR to Mobile IR. Chapter
4 presents an overview of the document collections that are searchable by a
Mobile IR system, and that are somehow different from classical IR ones;
available for experimentation, including collections of data that have become
complementary to Mobile IR. Similarly, Chapter 5 reviews mobile information
needs studies and users log analysis. Chapter 6 reviews studies aimed at
adapting and improving the users interface to the needs of Mobile IR. Chapter
7, instead, reviews work on context awareness, which studies the many aspects
of the user context that Mobile IR employs. Chapter 8 reviews some of
evaluation work done in Mobile IR, highlighting the distinctions with classical
IR from the perspectives of two main IR evaluation methodologies: users studies
and test collections. Finally, Chapter 9 reports the conclusions of this
review, highlighting briefly some trends in Mobile IR that we believe will
drive research in the next few years.Comment: 116 pages, published in 201
Internet Advertising: An Interplay among Advertisers, Online Publishers, Ad Exchanges and Web Users
Internet advertising is a fast growing business which has proved to be
significantly important in digital economics. It is vitally important for both
web search engines and online content providers and publishers because web
advertising provides them with major sources of revenue. Its presence is
increasingly important for the whole media industry due to the influence of the
Web. For advertisers, it is a smarter alternative to traditional marketing
media such as TVs and newspapers. As the web evolves and data collection
continues, the design of methods for more targeted, interactive, and friendly
advertising may have a major impact on the way our digital economy evolves, and
to aid societal development.
Towards this goal mathematically well-grounded Computational Advertising
methods are becoming necessary and will continue to develop as a fundamental
tool towards the Web. As a vibrant new discipline, Internet advertising
requires effort from different research domains including Information
Retrieval, Machine Learning, Data Mining and Analytic, Statistics, Economics,
and even Psychology to predict and understand user behaviours. In this paper,
we provide a comprehensive survey on Internet advertising, discussing and
classifying the research issues, identifying the recent technologies, and
suggesting its future directions. To have a comprehensive picture, we first
start with a brief history, introduction, and classification of the industry
and present a schematic view of the new advertising ecosystem. We then
introduce four major participants, namely advertisers, online publishers, ad
exchanges and web users; and through analysing and discussing the major
research problems and existing solutions from their perspectives respectively,
we discover and aggregate the fundamental problems that characterise the
newly-formed research field and capture its potential future prospects.Comment: 44 pages, 7 figures, 6 tables. Submitted to Information Processing
and Managemen
A Survey on Content-Aware Video Analysis for Sports
Sports data analysis is becoming increasingly large-scale, diversified, and
shared, but difficulty persists in rapidly accessing the most crucial
information. Previous surveys have focused on the methodologies of sports video
analysis from the spatiotemporal viewpoint instead of a content-based
viewpoint, and few of these studies have considered semantics. This study
develops a deeper interpretation of content-aware sports video analysis by
examining the insight offered by research into the structure of content under
different scenarios. On the basis of this insight, we provide an overview of
the themes particularly relevant to the research on content-aware systems for
broadcast sports. Specifically, we focus on the video content analysis
techniques applied in sportscasts over the past decade from the perspectives of
fundamentals and general review, a content hierarchical model, and trends and
challenges. Content-aware analysis methods are discussed with respect to
object-, event-, and context-oriented groups. In each group, the gap between
sensation and content excitement must be bridged using proper strategies. In
this regard, a content-aware approach is required to determine user demands.
Finally, the paper summarizes the future trends and challenges for sports video
analysis. We believe that our findings can advance the field of research on
content-aware video analysis for broadcast sports.Comment: Accepted for publication in IEEE Transactions on Circuits and Systems
for Video Technology (TCSVT
Issues Related to the Emergence of the Information Superhighway and California Societal Changes, IISTPS Report 96-4
The Norman Y. Mineta International Institute for Surface Transportation Policy Studies (IISTPS) at San José State University (SJSU) conducted this project to review the continuing development of the Internet and the Information Superhighway. Emphasis was placed on an examination of the impact on commuting and working patterns in California, and an analysis of how public transportation agencies, including Caltrans, might take advantage of the new communications technologies. The document reviews the technology underlying the current Internet “structure” and examines anticipated developments. It is important to note that much of the research for this limited-scope project was conducted during 1995, and the topic is so rapidly evolving that some information is almost automatically “dated.” The report also examines how transportation agencies are basically similar in structure and function to other business entities, and how they can continue to utilize the emerging technologies to improve internal and external communications. As part of a detailed discussion of specific transportation agency functions, it is noted that the concept of a “Roundtable Forum,” growing out of developments in Concurrent Engineering, can provide an opportunity for representatives from multiple jurisdictions to utilize the Internet for more coordinated decision-making. The report also included an extensive analysis of demographic trends in California in recent years, such as commute and recreational activities, and identifies how the emerging technologies may impact future changes
Inferring Human Traits From Facebook Statuses
This paper explores the use of language models to predict 20 human traits
from users' Facebook status updates. The data was collected by the
myPersonality project, and includes user statuses along with their personality,
gender, political identification, religion, race, satisfaction with life, IQ,
self-disclosure, fair-mindedness, and belief in astrology. A single
interpretable model meets state of the art results for well-studied tasks such
as predicting gender and personality; and sets the standard on other traits
such as IQ, sensational interests, political identity, and satisfaction with
life. Additionally, highly weighted words are published for each trait. These
lists are valuable for creating hypotheses about human behavior, as well as for
understanding what information a model is extracting. Using performance and
extracted features we analyze models built on social media. The real world
problems we explore include gendered classification bias and Cambridge
Analytica's use of psychographic models.Comment: Submitted to the International Conference on Social Informatics 201
Special Libraries, Winter 1986
Volume 77, Issue 1https://scholarworks.sjsu.edu/sla_sl_1986/1000/thumbnail.jp
From Data Harvesting to Querying for Making Urban Territories Smart
This chapter provides a summarized, critical and analytical point of view of
the data-centric solutions that are currently applied for addressing urban
problems in cities. These solutions lead to the use of urban computing
techniques to address their daily life issues. Data-centric solutions have
become popular due to the emergence of data science. The chapter describes and
discusses the type of urban challenges and how data science in urban computing
can face them. Current solutions address a spectrum that goes from data
harvesting techniques to decision making support. Finally, the chapter also
puts in perspective families of strategies developed in the state of the art
for addressing urban problems and exhibits guidelines that can lead to a
methodological understanding of these strategies
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