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

This paper presents a “time-stamped authoring graph”, which is a new video description model and retrieval method based on fragmentary descriptions of video contents (i.e., the authors' impressions or feelings) and their relationships. It. can handle continuous video images better than existing description models, which tend to have problems in extracting parts of continuous video images and giving them precise descriptions. A video retrieval algorithm using a time-stamped authoring graph is explained, and the criteria for selecting or ranking the retrieved video images are discussed. The design and implementation of the prototype for video description and retrieval interfaces are also described and examined, with some examples.

A Time-Stamped Authoring Graph for Video Databases

In this paper, we propose a change monitoring/notification system WebSCAN (Web Sites Change Analyzer and Notifier) for Web, which monitors and analyzes the change of pre-registered Web sites and notifies important changes to users by a push-type delivery mechanism.

WebSCAN: Discovering and Notifying Important Changes of Web Sites

Animated text, commonly called kinetic typography, is any attractive visual expression used in films, TV programs, video games, etc. Previous studies have developed tools that support the authoring and rendering of kinetic typography. However, authoring kinetic typography is not easy because its methodology is still at an early stage. Hence, we systematize expression elements in kinetic typography and propose an automatic composer that converts raw text into kinetic typography data.

Automatic kinetic typography composer

Although many studies have addressed the problem of finding Web pages seeking relevant and popular information from a query, very few have focused on the discovery of unexpected information. This paper provides and evaluates methods for discovering unexpected information for a keyword query. For example, if the user inputs "Michael Jackson," our system first discovers the unexpected related term "karate" and then returns the unexpected information "Michael Jackson is good at karate." Discovering unexpected information is useful in many situations. For example, when a user is browsing a news article on the Web, unexpected information about a person associated with the article can pique the user's interest. If a user is sightseeing or driving, providing unexpected, additional information about a building or the region is also useful. Our approach collects terms related to a keyword query and evaluates the degree of unexpectedness of each related term for the query on the basis of (i) the relationships of coordinate terms of both the keyword query and related terms, and (ii) the degree of popularity of each related term. Experimental results show that considering these two factors are effective for discovering unexpected information.

Discovering unexpected information on the basis of popularity/unpopularity analysis of coordinate objects and their relationships

We propose and implement methods for making collaborative searches more efficient in mobile computing environments. In mobile collaborative searches, the small screens of mobile devices make it difficult to share information such as discovered Web pages, evaluations of these, and information related to their search topics. We propose and implement a system supporting mobile collaborative searches, which provides a function for informing others about Web pages by inserting them into others' search results using simple actions; a function of displaying information related to others' search topics; and a function of showing the most positively evaluated Web pages at the top of the list of discovered Web pages. We also propose a method for the system to create a group of mobile devices easily. The results of evaluation tests show these methods support the sharing of information and improve the users' satisfaction.

Katsumi Tanaka

Papers

A Time-Stamped Authoring Graph for Video Databases

WebSCAN: Discovering and Notifying Important Changes of Web Sites

Automatic kinetic typography composer

Discovering unexpected information on the basis of popularity/unpopularity analysis of coordinate objects and their relationships

Supporting sharing of browsing information and search results in mobile collaborative searches