Determining the User Intent of Chinese-English Mixed Language Queries Based On Search Logs

With the increasing number of multilingual web pages on the Internet, multilingual information retrieval has become an important research topic. While queries are the key element of information retrieval process, mixed-language queries have not yet been adequately studied. This study is to determine the user intents of Chinese-English mixed-language queries submitted to a Chinese search engine, and compares the user intents identified by query content to those identified using additional user behavior data (e.g. clicked results, subsequent queries). The preliminary findings present the distributions of user intents by analyzing query only and additional user behavior data, suggesting a specific searching behavior of Chinese-English mixed-language queries users. The findings of this study could provide useful insights in understanding the searching behavior of Chinese-English mixed-language queries users, and enable web search engines to provide users with more relevant results and more precisely targeted sponsored links.ye

Mining the Query Logs of a Chinese Web Search Engine for Character Usage Analysis

The use of non-English Web search engines has been prevalent. Given the popularity of Chinese Web searching and the unique characteristics of Chinese language, it is imperative to conduct studies with focuses on the analysis of Chinese Web search queries. In this paper, we report our research on the character usage of Chinese search logs from Web search engine in Hong Kong. By examining the distribution of search queries terms, we found that people intended to use more diversified terms and that the usage of characters in search queries was quite different from the character usage of both general online information in Chinese and Web search queries in English. We believe the findings from this study have provided some insights into further research in non-English Web searching and will assist in the design of more effective Chinese Website search engines

Global disease monitoring and forecasting with Wikipedia

Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data such as social media and search queries are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with $r^2$ up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.Comment: 27 pages; 4 figures; 4 tables. Version 2: Cite McIver & Brownstein and adjust novelty claims accordingly; revise title; various revisions for clarit

Mnews: A Study of Multilingual News Search Interfaces

With the global expansion of the Internet and the World Wide Web, users are becoming increasingly diverse, particularly in terms of languages. In fact, the number of polyglot Web users across the globe has increased dramatically. However, even such multilingual users often continue to suffer from unbalanced and fragmented news information, as traditional news access systems seldom allow users to simultaneously search for and/or compare news in different languages, even though prior research results have shown that multilingual users make significant use of each of their languages when searching for information online. Relatively little human-centered research has been conducted to better understand and support multilingual user abilities and preferences. In particular, in the fields of cross-language and multilingual search, the majority of research has focused primarily on improving retrieval and translation accuracy, while paying comparably less attention to multilingual user interaction aspects. The research presented in this thesis provides the first large-scale investigations of multilingual news consumption and querying/search result selection behaviors, as well as a detailed comparative analysis of polyglots’ preferences and behaviors with respect to different multilingual news search interfaces on desktop and mobile platforms. Through a set of 4 phases of user studies, including surveys, interviews, as well as task-based user studies using crowdsourcing and laboratory experiments, this thesis presents the first human-centered studies in multilingual news access, aiming to drive the development of personalized multilingual news access systems to better support each individual user

GAUGING PUBLIC INTEREST FROM SERVER LOGS, SURVEYS AND INLINKS

As the World Wide Web (the Web) has turned into a full-fledged medium to disseminate news, it is very important for journalism and information science researchers to investigate how Web users access online news reports and how to interpret such usage patterns. This doctoral thesis collected and analyzed Web server log statistics, online surveys results, online reprints of the top 50 news reports, as well as external inlinks data of a leading comprehensive online newspaper (the People’s Daily Online) in China, one of the biggest Web/information markets in today’s world. The aim of the thesis was to explore various methods to gauge the public interest from a Webometrics perspective. A total of 129 days of Web server log statistics, including the top 50 Chinese and English news stories with the highest daily pageview numbers, the comments attracted by these news items and the emailed frequencies of the same stories were collected from October 2007 to September 2008. These top 50 news items’positions on the Chinese and English homepages and the top 50 queries submitted to the website search engine of the People’s Daily Online were also retrieved. Results of the two online surveys launched in March 2008 and March 2009 were collected after their respective closing dates. The external inlinks to the People’s Daily Online were retrieved by Yahoo! (Chinese and English versions), and the online reprints were retrieved by Google. Besides the general usage patterns identified from the top 50 news stories, this study, by conducting statistical tests on the data sets, also reveals the following findings. First, the editors’ choices and the readers’ favorites do not always match each other; thus content of news title is more important than its homepage position in attracting online visits. Second, the Chinese and English readers’ interests in the same events are different. Third, the pageview numbers and comments posted to the news items reflect the unfavorable attitudes of the Chinese people toward the United States and Japan, which might offer us a method to investigate the public interest in some other issues or nations after necessary modifications. More importantly, some publicly available data, such as the comments posted to the news stories and online survey results, further show that the pageview measure does reflect readers’ interests/needs truthfully, as proved by the strong correlations between the top news reports and relevant top queries. The external ininks to the news websites and the online reprints of the top news items help us examine readers\u27 interests from other perspectives, as well as establish online profiles of the news websites. Such publicly accessible information could be an alternative data source for researchers to study readers\u27 interests when the Web server log data are not available. This doctoral thesis not only shows the usefulness of Web server log statistics, survey results, and other publicly accessible data in studying Web user’s information needs, but also offers practical suggestions for online news sites to improve their contents and homepage designs. However, no single method can draw a complete picture of the online news readers’ interests. The above mentioned research methodologies should be employed together, in order to make more comprehensive conclusions. Future research is especially needed to investigate the continuously rapid growth of the “Mobile News Readers,” which poses both challenges and opportunities to the press industry in the 21st century

GAUGING PUBLIC INTEREST FROM SERVER LOGS, SURVEYS AND INLINKS A Multi-Method Approach to Analyze News Websites

As the World Wide Web (the Web) has turned into a full-fledged medium to disseminate news, it is very important for journalism and information science researchers to investigate how Web users access online news reports and how to interpret such usage patterns. This doctoral thesis collected and analyzed Web server log statistics, online surveys results, online reprints of the top 50 news reports, as well as external inlinks data of a leading comprehensive online newspaper (the People\u27s Daily Online) in China, one of the biggest Web/information markets in today\u27s world. The aim of the thesis was to explore various methods to gauge the public interest from a Webometrics perspective. A total of 129 days of Web server log statistics, including the top 50 Chinese and English news stories with the highest daily pageview numbers, the comments attracted by these news items and the emailed frequencies of the same stories were collected from October 2007 to September 2008. These top 50 news items’positions on the Chinese and English homepages and the top 50 queries submitted to the website search engine of the People’s Daily Online were also retrieved. Results of the two online surveys launched in March 2008 and March 2009 were collected after their respective closing dates. The external inlinks to the People’s Daily Online were retrieved by Yahoo! (Chinese and English versions), and the online reprints were retrieved by Google. Besides the general usage patterns identified from the top 50 news stories, this study, by conducting statistical tests on the data sets, also reveals the following findings. First, the editors’ choices and the readers’ favorites do not always match each other; thus content of news title is more important than its homepage position in attracting online visits. Second, the Chinese and English readers’ interests in the same events are different. Third, the pageview numbers and comments posted to the news items reflect the unfavorable attitudes of the Chinese people toward the United States and Japan, which might offer us a method to investigate the public interest in some other issues or nations after necessary modifications. More importantly, some publicly available data, such as the comments posted to the news stories and online survey results, further show that the pageview measure does reflect readers’ interests/needs truthfully, as proved by the strong correlations between the top news reports and relevant top queries. The external ininks to the news websites and the online reprints of the top news items help us examine readers\u27 interests from other perspectives, as well as establish online profiles of the news websites. Such publicly accessible information could be an alternative data source for researchers to study readers\u27 interests when the Web server log data are not available. This doctoral thesis not only shows the usefulness of Web server log statistics, survey results, and other publicly accessible data in studying Web user’s information needs, but also offers practical suggestions for online news sites to improve their contents and homepage designs. However, no single method can draw a complete picture of the online news readers’ interests. The above mentioned research methodologies should be employed together, in order to make more comprehensive conclusions. Future research is especially needed to investigate the continuously rapid growth of the “Mobile News Readers,” which poses both challenges and opportunities to the press industry in the 21st century

Mixed-Language Arabic- English Information Retrieval

Includes abstract.Includes bibliographical references.This thesis attempts to address the problem of mixed querying in CLIR. It proposes mixed-language (language-aware) approaches in which mixed queries are used to retrieve most relevant documents, regardless of their languages. To achieve this goal, however, it is essential firstly to suppress the impact of most problems that are caused by the mixed-language feature in both queries and documents and which result in biasing the final ranked list. Therefore, a cross-lingual re-weighting model was developed. In this cross-lingual model, term frequency, document frequency and document length components in mixed queries are estimated and adjusted, regardless of languages, while at the same time the model considers the unique mixed-language features in queries and documents, such as co-occurring terms in two different languages. Furthermore, in mixed queries, non-technical terms (mostly those in non-English language) would likely overweight and skew the impact of those technical terms (mostly those in English) due to high document frequencies (and thus low weights) of the latter terms in their corresponding collection (mostly the English collection). Such phenomenon is caused by the dominance of the English language in scientific domains. Accordingly, this thesis also proposes reasonable re-weighted Inverse Document Frequency (IDF) so as to moderate the effect of overweighted terms in mixed queries

A Personalized System for Conversational Recommendations

Searching for and making decisions about information is becoming increasingly difficult as the amount of information and number of choices increases. Recommendation systems help users find items of interest of a particular type, such as movies or restaurants, but are still somewhat awkward to use. Our solution is to take advantage of the complementary strengths of personalized recommendation systems and dialogue systems, creating personalized aides. We present a system -- the Adaptive Place Advisor -- that treats item selection as an interactive, conversational process, with the program inquiring about item attributes and the user responding. Individual, long-term user preferences are unobtrusively obtained in the course of normal recommendation dialogues and used to direct future conversations with the same user. We present a novel user model that influences both item search and the questions asked during a conversation. We demonstrate the effectiveness of our system in significantly reducing the time and number of interactions required to find a satisfactory item, as compared to a control group of users interacting with a non-adaptive version of the system

Finding viable seed URLs for web corpora: A scouting approach and comparative study of available sources

International audienceThe conventional tools of the "web as corpus" framework rely heavily on URLs obtained from search engines. Recently, the corresponding querying process became much slower or impossible to perform on a low budget. I try to find acceptable substitutes, i.e. viable link sources for web corpus construction. To this end, I perform a study of possible alternatives, including social networks as well as the Open Directory Project and Wikipedia. Four different languages (Dutch, French, Indonesian and Swedish) taken as examples show that complementary approaches are needed. My scouting approach using open-source software leads to a URL directory enriched with metadata which may be used to start a web crawl. This is more than a drop-in replacement for existing tools since said metadata enables researchers to filter and select URLs that fit particular needs, as they are classified according to their language, their length and a few other indicators such as host- and markup-based data

Writing/thinking in real time: digital video and corpus query analysis

The advance of digital video technology in the past two decades facilitates empirical investigation of learning in real time. The focus of this paper is the combined use of real-time digital video and a networked linguistic corpus for exploring the ways in which these technologies enhance our capability to investigate the cognitive process of learning. A perennial challenge to research using digital video (e.g., screen recordings) has been the method for interfacing the captured behavior with the learners’ cognition. An exploratory proposal in this paper is that with an additional layer of data (i.e., corpus search queries), analyses of real-time data can be extended to provide an explicit representation of learner’s cognitive processes. This paper describes the method and applies it to an area of SLA, specifically writing, and presents an in-depth, moment-by-moment analysis of an L2 writer’s composing process. The findings show that the writer’s composing process is fundamentally developmental, and that it is facilitated in her dialogue-like interaction with an artifact (i.e., the corpus). The analysis illustrates the effectiveness of the method for capturing learners’ cognition, suggesting that L2 learning can be more fully explicated by interpreting real-time data in concert with investigation of corpus search queries