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.

/pdf/opinion-mining-and-sentiment-analysis-3v5ya3qqiw.pdf

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

A video-object data model and the design and implementation of a prototype video-object database system named OVID based on the model are described. Notable features of the video-object data model are a mechanism to share common descriptional data among video-objects, called interval-inclusion based inheritance, and operations to composite video-objects. The OVID system offers a browsing/inspection tool called VideoChart, and adhoc query facility called VideoSQL, and a video-object definition tool. >

OVID: design and implementation of a video-object database system

Social bookmarking is an emerging type of a Web service that helps users share, classify, and discover interesting resources. In this paper, we explore the concept of an enhanced search, in which data from social bookmarking systems is exploited for enhancing search in the Web. We propose combining the widely used link-based ranking metric with the one derived using social bookmarking data. First, this increases the precision of a standard link-based search by incorporating popularity estimates from aggregated data of bookmarking users. Second, it provides an opportunity for extending the search capabilities of existing search engines. Individual contributions of bookmarking users as well as the general statistics of their activities are used here for a new kind of a complex search where contextual, temporal or sentiment-related information is used. We investigate the usefulness of social bookmarking systems for the purpose of enhancing Web search through a series of experiments done on datasets obtained from social bookmarking systems. Next, we show the prototype system that implements the proposed approach and we present some preliminary results.

Can social bookmarking enhance search in the web

In this paper, we propose a system for helping users to judge the credibility of Web search results and to search for credible Web pages. Conventional Web search engines present only titles, snippets, and URLs for users, which give few clues to judge the credibility of Web search results. Moreover, ranking algorithms of the conventional Web search engines are often based on relevance and popularity of Web pages. Towards credibility-oriented Web search, our proposed system provides users with the following three functions: (1) calculation and visualization of several scores of Web search results on the main credibility aspects, (2) prediction of user's credibility judgment model through user's credibility feedback for Web search results, and (3) re-ranking of Web search results based on user's predicted credibility model. Experimental results suggest that our system enables users - in particular, users with knowledge about search topics - to find credible Web pages from a list of Web search results more efficiently than conventional Web search interfaces.

Enhancing credibility judgment of web search results

Increased usage of Web search engines in our daily lives means that the trustworthiness of searched results has become crucial User studies on the usage of search engines and analysis of the factors used to determine trust that users have in search results are described in this paper Based on the analysis, we developed a system to help users determine the trustworthiness of Web search results by computing and showing each returned page's topic majority, topic coverage, locality of supporting pages (ie, pages linked to each search result) and other information The measures proposed in the paper can be applied to the search of Web-based libraries or can be useful in the usage of digital library search systems

/pdf/trustworthiness-analysis-of-web-search-results-50kclsqqmp.pdf

Trustworthiness analysis of web search results

A blog (weblog) lets people promptly publish content (such as comments) relating to other blogs through hyperlinks. This type of web content can be considered as a conversation rather than a collection of archived document. To capture ’hot’ conversation topics from blogs and deliver them to users in a timely manner, we propose a method of discovering bloggers who take an important role in conversations. We characterize bloggers based on their roles in previous blog threads (a set of blog entries comprises a conversation),. We provide several definitions of bloggers’ roles including (1) agitators who stimulate discussion, and (2) summarizers who provide summaries of the discussion. We consider that these bloggers are likely to be useful in identifying hot conversations. In this paper, we discuss models of blogs and blog thread data, and methods of extracting blog threads, discovering important bloggers, and acquiring important content from their entries.

/pdf/discovering-important-bloggers-based-on-analyzing-blog-2qmgto8vru.pdf

Katsumi Tanaka

Papers

OVID: design and implementation of a video-object database system

Can social bookmarking enhance search in the web

Enhancing credibility judgment of web search results

Trustworthiness analysis of web search results

Discovering Important Bloggers based on Analyzing Blog Threads