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

This paper proposes a content and device management method for multiple contents browsing with multiple devices. We introduce Content Management Description and Device Management Description; the former is used to determine what content to distribute to the device and how to present it, while the latter is used to determine the current status of devices available for browsing content. By analyzing them, contents are distributed and effectively presented on their respective devices. This method is expected to achieve effective browsing of contents with multiple devices in users preferred styles.

A Content and Device Management Method for Multiple Contents Browsing with Multiple Devices

It is our great pleasure to welcome you all to the 2nd Workshop on Information Credibility on the Web (WICOW'08). The aim of the workshop is to provide a forum for discussion on issues related to information credibility criteria and the process of its evaluation.

The web has started to play an important role for many people in delivering information related to their personal and professional lives. However, there is usually inadequate quality control of web content,and, in fact, virtually anyone can publish anything on the web. This calls for methodologies that would facilitate judging the trustworthiness of content that users encounter on the web. Related issue is the analysis of user behavior and, in particular, the factors to which users pay attention when evaluating the credibility of information. In general, the information credibility is a complex, multi-dimensional issue and the effective methods for judging content's trustworthiness should combine technologies from diverse research areas such as information retrieval and extraction, information processing, web search, knowledge representation, etc. Through this workshop we hope to exchange novel ideas and findings as well as promote discussions on various aspects of information credibility.

We have received submissions from 5 continents: Africa, Asia, Australia, Europe and North America. After a careful review process, with at least three reviews for each paper, the program committee has selected 9 full and 6 short papers covering a variety of topics related to information credibility. The accepted papers were thematically grouped into 4 sessions: "Analyzing social networks and discussion forums", "Web content analysis", "Content aggregation on the web" and "Information quality: frameworks and theories". In addition, we are pleased to invite two keynote speakers. The first keynote talk entitled: "Graph Mining and Influence Propagation" will be delivered by Christos Faloutsos from Carnegie Mellon University, USA. Yutaka Kidawara from National Institute of Information and Communications Technology, Japan will give the second keynote talk entitled: "Information Credibility Analysis of Web Content".

Proceedings of the 2nd ACM workshop on Information credibility on the web

Users of existing Web information retrieval systems need to input proper keywords through which the correct retrieval data can be found. It is, however, too difficult for children to identify appropriate keywords due to their lack of ability in generalizing concepts describing what they would like to search for: Therefore, a great deal of irrelevant data is included in the results. In the paper, we propose a "Kid's Lifestyle Ontology" so that the system can infer what they would like to search for to resolve ambiguities. The retrieval system can identify appropriate keywords that have strong relationships with concepts common to their lifestyles, and then the related search keywords can be ranked above other keywords. This is based on the episodic memories of children that help them discover other keywords. As a result, children can rejne their queries gradually. In the paper, we also propose a method of constructing the ontology incrementally and recursively.

Web Information Retrieval Using Ontology for Children Based on their Lifestyles

We address the problem of entity identification on a microblog with special attention to indirect reference cases in which entities are not referred to by their names. Most studies on identifying entities referred to them by their full/partial name or abbreviation, while there are many indirectly mentioned entities in microblogs, which are difficult to identify in short text such as microblogs. We therefore tackled indirect reference cases by developing features that are particularly important for certain types of indirect references and modeling dependency among referred entities by a Conditional Random Field (CRF) model. In addition, we model non-sequential order dependency while keeping the inference tractable by dynamically building dependency among entities. The experimental results suggest that our features were effective for indirect references, and our CRF model with adaptive dependency was robust even when there were multiple mentions in a microblog and achieved the same high performance as that with the fully connected CRF model. key words: entity identification, indirect reference, Conditional Random Field

Entity Identification on Microblogs by CRF Model with Adaptive Dependency

Recently, it is getting more frequent to search not Web contents but local contents, e.g., by Google Desktop Search. Google succeeded in the Web search because of its PageRank algorithm for the ranking of the search results. PageRank estimates the quality of Web pages based on their popularity, which in turn is estimated by the number and the quality of pages referring to them through hyperlinks. This algorithm, however, is not applicable when we search local contents without link structure, such as text data. In this research, we propose a method to estimate the quality of local contents without link structure by using the PageRank values of Web contents similar to them. Based on this estimation, we can rank the desktop search results. Furthermore, this method enables us to search contents across different resources such as Web contents and local contents. In this paper, we applied this method to Web contents, calculated the scores that estimate their quality, and we compare them with their page quality scores by PageRank.

http://delab.csd.auth.gr/~dimitris/courses/ir_spring06/page_rank_computing/01623929.pdf

Katsumi Tanaka

Papers

A Content and Device Management Method for Multiple Contents Browsing with Multiple Devices

Proceedings of the 2nd ACM workshop on Information credibility on the web

Web Information Retrieval Using Ontology for Children Based on their Lifestyles

Entity Identification on Microblogs by CRF Model with Adaptive Dependency

Quality Estimation of Local Contents Based on PageRank Values of Web Pages