Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Data Mining - Concepts and Techniques.

An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people now can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object.

This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. Our focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. We include material on summarization of evaluative text and on broader issues regarding privacy, manipulation, and economic impact that the development of opinion-oriented information-access services gives rise to. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided.

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Opinion Mining and Sentiment Analysis

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

We present a system for interactively browsing and exploring large unstructured collections of photographs of a scene using a novel 3D interface. Our system consists of an image-based modeling front end that automatically computes the viewpoint of each photograph as well as a sparse 3D model of the scene and image to model correspondences. Our photo explorer uses image-based rendering techniques to smoothly transition between photographs, while also enabling full 3D navigation and exploration of the set of images and world geometry, along with auxiliary information such as overhead maps. Our system also makes it easy to construct photo tours of scenic or historic locations, and to annotate image details, which are automatically transferred to other relevant images. We demonstrate our system on several large personal photo collections as well as images gathered from Internet photo sharing sites.

Photo tourism: exploring photo collections in 3D

We define "Secure Space" as a physical space in which any resource is always protected from its unauthorized users in terms of enforcing its authorization policies assuredly. Aiming to build such secure spaces, this paper proposes an architecture and a model for space entry control based on its dynamically changing contents, such as users, physical resources and virtual resources outputted by some embedded devices. We first describe the architecture and then formalize the model and mechanism for secure spaces.

Content-Based Entry Control for Secure Spaces

With the growing amount of information on the WWW and the improvement of mobile computing environments, mobile Web search engines will increase significance or more in the future. Because mobile devices have the restriction of output performance and we have little time for browsing information slowly while moving or doing some activities in the real world, it is necessary to refine the retrieval results in mobile computing environments better than in fixed ones. However, since a mobile users query is often shorter and more ambiguous than a fixed users query which is not enough to guess his/her information demand accurately, too many results might be retrieved by commonly used Web search engines. This paper proposes two novel methods for query modification based on real-world contexts of a mobile user, such as his/her geographic location and the objects surrounding him/her, aiming to enhance location-awareness, and moreover, context-awareness, to the existing location-free information retrieval systems.

Query Modification Based on Real-World Contexts for Mobile and Ubiquitous Computing Environments

One of the main problems of delivering online course materials to learners lies in a deficiency of search capability. We propose a method for querying inside lecture materials exploiting a textbook ontology, which is automatically constructed from a back-of-the-book index and table of contents. The use of a textbook ontology is two-fold: (i) to help users formulate query more efficiently, and (ii) to discriminate query results that are relevant to user information needs from those that merely contain query terms but are not informative.

Context-aware search inside e-learning materials using textbook ontologies

Social Network Services (SNS) have been recently commonly used for collecting and inferring user-related information. As SNS users leave multiple traces of their activities and thoughts, it has become possible to predict their future actions, e.g., a trip to a far-away destination or a purchase of a certain product. In this paper, we approach the latter problem and attempt to predict purchasing actions of Twitter users. In particular, we focus on the task of purchase prediction of two product categories: digital cameras and personal computers. The results suggest the feasibility of prediction when using relatively simple features collected from user tweeting histories as well as from their social contexts.

Katsumi Tanaka

Papers

Content-Based Entry Control for Secure Spaces

Query Modification Based on Real-World Contexts for Mobile and Ubiquitous Computing Environments

Context-aware search inside e-learning materials using textbook ontologies

Product Purchase Prediction Based on Time Series Data Analysis in Social Media

Abstraction and Inheritance of HyperLinks in an Object-Oriented Hypertext Database System TextLink/Gem