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

Advances in dynamic map interfaces have turned maps into interactive media These dynamic interfaces respond to users' operations in real time, and present fully visualized geographic information However, the current systems have only reacted to explicitly specified user intentions For example, users have been required to elaborately specify visible layers to fully utilize a map interface In contrast, we propose a method of adjusting the way a map interface is presented by estimating the users' intentions based on their operation history By reducing their operations, the system facilitates the use of maps especially for novices It is especially effective in online or mobile map interfaces, where it is difficult to adjust the presentation of the map interface, due to the limited bandwidth and the size of the interface This paper specifically focuses on the trajectory, which is a series of panning operations, and discusses our inference of users' implicit intentions

Presentation of dynamic maps by estimating user intentions from operation history

When a user searches the Web for information about a target object by submitting a keyword-based query to such a conventional Web search engine as Google, the precision and recall of the search results depend a great deal on whether or not s/he has known exactly the concrete name of the target object. However, the user does not always know the concrete name of any target object that s/he has encountered in the real world and wanted information about. In this paper, we propose an application system of Object-Name Search that helps her/him to identify the concrete name of the target object by such ambiguous features as its class-name, visual appearance and spatio-temporal information. When the user inputs a class-name, visual appearance and/or real-world context descriptions, our system returns not only concrete object-names ranked by her/his specification but also their typical images, visual appearance and spatio-temporal descriptions. And then the user can also modify her/his original specification repeatedly by using their typical features as a useful reference.

Object-name search by visual appearance and spatio-temporal descriptions

A web page is referred to by other pages through links in various contexts, and these contexts indicate the “customer’s viewpoint” for the page. The references are called “aspects” of a web page, as distinguished from the content of the page. In this paper, we propose an approach for discovering aspects to characterize web pages based on their referential context. Based on the logical structure of the web (i.e., the web document structure and link structure), our approach discovers the appropriate range of surrounding contents and assigns them as the context of the web page. The aspects of the web page are discovered by clustering multiple contexts so that each aspect represents a “typical reference” to the page. The aspect can be used to strengthen the usability and credibility of a web page.

Aspect Discovery: Web Contents Characterization by Their Referential Contexts

In this paper, we introduce a method of spatial presentation of georeferenced data in a three-dimensional space. Photographs, Quicktime VRs, videos, and computer graphic renderings provide realistic presentations rich in visual information. We believe, however, there is an issue of visualizing georeferenced data such as attribute data for spatial objects as well as showing the objects themselves. We introduce an orientation-based visualization model for visualizing georeferenced data, and discuss abstraction of the georeferenced data through their spatial aggregation in the space specified by a user.

Katsumi Tanaka

Papers

Presentation of dynamic maps by estimating user intentions from operation history

Object-name search by visual appearance and spatio-temporal descriptions

Aspect Discovery: Web Contents Characterization by Their Referential Contexts

Spatial presentation and aggregation of georeferenced data

Web OpinionPoll: Extensive Collection and Impression-based Visualization of People’s Opinions