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

We previously proposed a reranking system for Web searches based on user interaction. The system encouraged users to interact with terms in search results or with frequent terms displayed in the tagcloud visualization style. Over 20,000 interaction logs of users were analyzed, and the results showed that more than 70% of users had interacted with the terms in the tagcloud area. Therefore, this visualization style is thought to have great potential in supporting users in their Web searches. This visualization style is referred to as TermCloud in this paper. We describe how TermCloud can increase the effectiveness of users' Web searches, and we propose a technique to generate a more useful TermCloud than the frequency-based TermCloud. Then, we show the usefulness of our method based on the experimental test.

TermCloud for Enhancing Web Search

A browsing system is described for transforming declarative web content into humorous-dialogue TV-program-like content that is presented through character agent animation and synthesized speech. We call this system Web2Talkshow which enables users to obtain web content in a manner similar to watching TV. Web content is transformed into humorous dialogues based on the keywords-set of the web page. By using Web2Talkshow, users will be able to watch and listen to desired web content in an easy, pleasant, and userfriendly way, like watching a comedy show.

Web content transformed into humorous dialogue-based TV-program-like content

In this paper, we describe the extraction of Web knowledge from Web search engines and their usage for improving conventional Web search, such as supporting user's recall of vocabulary (query keywords), evaluation (quality, trustworthiness etc.) of search results, and re-ranking of search results. The extraction is based on the ideas of the "structural term co-occurrence" relationships and aggregating social annotation information, which can be easily computed by conventional Web search engines. Also, we describe a database interface to extract knowledge from Web search engines, which wraps accesses to Web search engines as virtual relational tables.

Web knowledge extraction for improving search

In recent years, the growth of the WWW has rapidly expanded and it’s not always easy to retrieve information. Search engines are very useful, but they treat each page as an independent document. In this paper, we propose an automatic navigation method that follows users’ requirements for Web sites. This method detects the essential pages in the site and generates an ordered list of pages that present results by applying page linkage information. Furthermore, we have designed and implemented a prototype system based on our proposed method.

Summarization and Presentation for Web Documents using Context Paths.

Knowledge of entity histories is often necessary for comprehensive understanding and characterization of entities. Yet, the analysis of an entity’s history is often most meaningful when carried out in comparison with the histories of other entities. In this paper, we describe a novel task of history-based entity categorization and comparison. Based on a set of entity-related documents which are assumed as an input, we determine latent entity categories whose members share similar histories; hence, we are effectively grouping entities based on the correspondences in their historical developments. Next, we generate comparative timelines for each determined group allowing users to elucidate similarities and differences in the histories of entities. We evaluate our approach on several datasets of different entity types demonstrating its effectiveness against competitive baselines.

/pdf/discovering-latent-threads-in-entity-histories-3zxijt05xs.pdf

Katsumi Tanaka

Papers

TermCloud for Enhancing Web Search

Web content transformed into humorous dialogue-based TV-program-like content

Web knowledge extraction for improving search

Summarization and Presentation for Web Documents using Context Paths.

Discovering Latent Threads in Entity Histories