Tour recommendations by mining photo sharing social media

2017 | Decision Support Systems | Citations: 5

Authors: Sun, Chih-Yuan; Lee, Anthony J. T.

Abstract: With the increasing popularity of photo and video sharing social networks, more ... Expand

Abstract: With the increasing popularity of photo and video sharing social networks, more and more people have shared their photos or videos with their family members and friends. Therefore, in this paper, we propose a framework for recommending top-k tours to meet user's interest and time frame by using user-generated contents in a photo sharing social network. The proposed framework contains four phases. First, we cluster geotagged locations into landmarks, and further cluster these landmarks into areas by the mean-shift clustering method. Second, we employ the Latent Dirichlet Allocation model to categorize the hashtags posted by users into landmark topics, and then use these topics to characterize landmarks and users. Third, to recommend tours for a user, we compute the tendency (or score) of the user visiting each landmark by the landmark popularity, the attraction of landmark to the user, and how many users similar to the user visit the landmark. Finally, based on the scores computed, we develop a method to recommend top-k tours with highest scores for the user. Unlike most previous methods recommending tours landmark by landmark, our framework recommends tours area by area so that users can avoid going back and forth from one area to another and save plenty of time on transportation, which in turn can visit more landmarks. The experiment results show that our proposed method outperforms the Markov-Topic method in terms of average score and precision. Our proposed framework may help users plan their trips and customize a trip for each user. Collapse

Topics: social network Flickr user-generated content user requirement application programming interface

Methods: experiment cluster analysis latent dirichlet allocation survey descriptive statistic

WNavis: Navigating Wikipedia semantically with an SNA-based summarization technique

2012 | Decision Support Systems | Citations: 0

Authors: Wu, I-Chin; Lin, Yi-Sheng

Abstract: Link-based applications like Wikipedia are becoming increasingly popular because ... Expand

Abstract: Link-based applications like Wikipedia are becoming increasingly popular because they provide users with an efficient way to find needed knowledge, such as searching for definitions and information about a particular topic, and exploring articles on related topics. This work introduces a semantics-based navigation application called WNavis, to facilitate information-seeking activities in internal link-based websites in Wikipedia. WNavis is based on the theories and techniques of link mining, semantic relatedness analysis and text summarization. Our goal is to develop an application that helps users find related articles for a seed query (topic) easily and then quickly check the content of articles to explore a new concept or topic in Wikipedia. Technically, we construct a preliminary topic network by analyzing the internal links of Wikipedia and applying the normalized Google distance algorithm to quantify the strength of the semantic relationships between articles via key terms. Because not all the content of articles in Wikipedia is relevant to users' information needs, it is desirable to locate specific information for users and enable them to quickly explore and read topic-related articles. Accordingly, we propose an SNA-based single and multiple-document summarization technique that can extract meaningful sentences from articles. We applied a number of intrinsic and extrinsic evaluation methods to demonstrate the efficacy of the summarization techniques in terms of precision, and recall. The results suggest that the proposed summarization technique is effective. Our findings have implications for the design of a navigation tool that can help users explore related articles in Wikipedia quickly. Collapse

Topics: Wikipedia website social network web page Google+

Methods: computational algorithm literature sample machine learning survey experiment

Theories: social network theory

An Event-Ontology-Based Approach to Constructing Episodic Knowledge from Unstructured Text Documents

2009 | International Conference on Information Systems | Citations: 0

Authors: Liang, Ting-Peng; Zhang, Dongsong; Lee, Ming-Yu

Abstract: Document summarization is an important function for knowledge management when a ... Expand

Abstract: Document summarization is an important function for knowledge management when a digital library of text documents grows. It allows documents to be presented in a concise manner for easy reading and understanding. Traditionally, document summarization adopts sentence-based mechanisms that identify and extract key sentences from long documents and assemble them together. Although that approach is useful in providing an abstract of documents, it cannot extract the relationship or sequence of a set of related events (also called episodes). This paper proposes an event-oriented ontology approach to constructing episodic knowledge to facilitate the understanding of documents. We also empirically evaluated the proposed approach by using instruments developed based on Bloom’s Taxonomy. The result reveals that the approach based on proposed event-oriented ontology outperformed the traditional text summarization approach in capturing conceptual and procedural knowledge, but the latter was still better in delivering factual knowledge. Collapse

Topics: knowledge representation online analytical processing information storage and retrieval system systems design online learning system

Methods: ontological modelling experiment design artifact document summarization design science

SpidersRUs: Creating specialized search engines in multiple languages

2008 | Decision Support Systems | Citations: 2

Authors: Chau, Michael; Qin, Jialun; Zhou, Yilu; Tseng, Chunju; Chen, Hsinchun

Abstract: While small-scale search engines in specific domains and languages are increasin ... Expand

Abstract: While small-scale search engines in specific domains and languages are increasingly used by Web users, most existing search engine development tools do not support the development of search engines in languages other than English, cannot be integrated with other applications, or rely on proprietary software. A tool that supports search engine creation in multiple languages is thus highly desired. To study the research issues involved, we review related literature and suggest the criteria for an ideal search tool. We present the design of a toolkit, called SpidersRUs, developed for multilingual search engine creation. The design and implementation of the tool, consisting of a Spider module, an Indexer module, an Index Structure, a Search module, and a Graphical User Interface module, are discussed in detail. A sample user session and a case study on using the tool to develop a medical search engine in Chinese are also presented. The technical issues involved and the lessons learned in the project are then discussed. This study demonstrates that the proposed architecture is feasible in developing search engines easily in different languages such as Chinese, Spanish, Japanese, and Arabic. Collapse

Topics: search engine Java web page healthcare data personal computer

Methods: case study cluster analysis parametric test experiment document summarization

Storyline-based summarization for news topic retrospection

2008 | Decision Support Systems | Citations: 0

Authors: Lin, Fu-ren; Liang, Chia-Hao

Abstract: Electronics newspapers gradually become main sources for news readers. When faci ... Expand

Abstract: Electronics newspapers gradually become main sources for news readers. When facing the numerous reports on a series of events in a topic, a summary of stories from news reports will benefit news readers in reviewing the news topic efficiently. Besides identifying events and presenting news titles and keywords the TDT (Topic Detection and Tracking) techniques are used to do, a summarized text to present event evolution is necessary for general news readers to review events under a news topic. This paper proposes a topic retrospection process and implements the SToRe (Story-line based Topic Retrospection) system that identifies various events under a news topic, and composes a summary that news readers can get the sketch of event evolution in the topic. It consists of three main functions: event identification, main storyline construction and storyline-based summarization. The constructed main storyline can remove the irrelevant events and present a main theme. The storyline-based summarization extracts the representative sentences and takes the main theme as the template to compose the summary. The storyline summary not only provides readers enough information to understand the development of a news topic, but also serves as an index for readers to search corresponding news reports. Following a design science paradigm, a lab experiment is conducted to evaluate the SToRe system in the question-and-answer (Q&A) setting. The experimental results show that SToRe enables news readers to effectively and efficiently capture the evolution of a news topic. Collapse

Topics: extensible markup language ease of use competitive intelligence digital news robotic

Methods: experiment experimental group computational algorithm Student's t-test parametric test

An information delivery system with automatic summarization for mobile commerce

2007 | Decision Support Systems | Citations: 1

Authors: Yang, Christopher C.; Wang, Fu Lee

Abstract: Wireless access with handheld devices is a promising addition to the WWW and tra ... Expand

Abstract: Wireless access with handheld devices is a promising addition to the WWW and traditional electronic business. Handheld devices provide convenience and portable access to the huge information space on the Internet without requiring users to be stationary with network connection. Many customer-centered m-services applications have been developed. The mobile computing, however, should be extended to decision support in an organization. There is a desire of accessing most update and accurate information on handheld devices for fast decision making in an organization. Unfortunately, loading and visualizing large documents on handheld devices are impossible due to their shortcomings. In this paper, we introduce the fractal summarization model for document summarization on handheld devices. Fractal summarization is developed based on the fractal theory. It generates a brief skeleton of summary at the first stage, and the details of the summary on different levels of the document are generated on demands of users. Such interactive summarization reduces the computation load in comparing with the generation of the entire summary in one batch by the traditional automatic summarization, which is ideal for wireless access. The three-tier architecture with the middle-tier conducting the major computation is also discussed. Visualization of summary on handheld devices is also investigated. The automatic summarization, the three-tier architecture, and the information visualization are potential solutions to the existing problems in information delivery to handheld devices for mobile commerce. Collapse

Topics: data visualization decision support mobile business internet technology system support

Methods: experiment exploratory data analysis descriptive statistic machine learning design artifact

Building a scientific knowledge web portal: The NanoPort experience

2006 | Decision Support Systems | Citations: 12

Authors: Chau, Michael; Huang, Zan; Qin, Jialun; Zhou, Yilu; Chen, Hsinchun

Abstract: There has been a tremendous growth in the amount of information and resources on ... Expand

Abstract: There has been a tremendous growth in the amount of information and resources on the World Wide Web that are useful to researchers and practitioners in science domains. While the Web has made the communication and sharing of research ideas and results among scientists easier and faster than ever, its dynamic and unstructured nature also makes the scientists faced with such problems as information overload, vocabulary difference, and lack of analysis tools. To address these problems, it is highly desirable to have an integrated, “one-stop shopping” Web portal to support effective information searching and analysis as well as to enhance communication and collaboration among researchers in various scientific fields. In this paper, we review existing information retrieval techniques and related literature, and propose a framework for developing integrated Web portals that support information searching and analysis for scientific knowledge. Our framework incorporates collection building, meta-searching, keyword suggestion, and various content analysis techniques such as document summarization, document clustering, and topic map visualization. Patent analysis techniques such as citation analysis and content map analysis are also incorporated. To demonstrate the feasibility of our approach, we developed based on our architecture a knowledge portal, called NanoPort, in the field of nanoscale science and engineering. We report our experience and explore the various issues of relevance to developing a Web portal for scientific domains. The system was compared to other search systems in the field and several design issues were identified. An evaluation study was conducted and the results showed that subjects were more satisfied with the NanoPort system than with Scirus, a leading search engine for scientific articles. Through our prototype system, we demonstrated the feasibility of using such an integrated approach and the study brought insight into applying the proposed domain-independent architecture to different areas of science and engineering in the future. Collapse

Topics: database system search engine information portal topic map web page

Methods: design artifact computational algorithm cluster analysis co-citation analysis qualitative content analysis

CMedPort: An integrated approach to facilitating Chinese medical information seeking

2006 | Decision Support Systems | Citations: 11

Authors: Zhou, Yilu; Qin, Jialun; Chen, Hsinchun

Abstract: As the number of non-English resources available on the Web is increasing rapidl ... Expand

Abstract: As the number of non-English resources available on the Web is increasing rapidly, developing information retrieval techniques for non-English languages is becoming an urgent and challenging issue. In this research to facilitate information seeking in a multilingual world, we focused on discovering how search-engine techniques developed for English could be generalized for use with other languages. We proposed a general framework incorporating a focused collection-building technique, a generic language processing ability, an integration of information resources, and a post-retrieval analysis module. Based on this approach, we developed CMedPort, a Chinese Web portal in the medical domain that not only allows users to search for Web pages from local collections and meta-search engines but also provides encoding conversion between simplified and traditional Chinese to support cross-regional search and document summarization and categorization. User studies were conducted to compare the effectiveness and efficiency of CMedPort with those of three major Chinese search engines. Results indicate that CMedPort achieved similar accuracy for search tasks, but exhibited significantly higher recall than each of the three search engines as well as higher precision than two of the search engines for browse tasks. There were no significant differences among the efficiency measures for CMedPort and benchmarks systems. A post-questionnaire regarding system usability indicated that CMedPort achieved significantly higher user satisfaction than any of the three benchmark systems. The subjects especially liked CMedPort's categorizer, commenting that it helped improve understanding of search results. These encouraging outcomes suggest a promising future for applying our approach to Internet searching and browsing in a multilingual world. Collapse

Topics: search engine internet technology usability user satisfaction web page

Methods: survey experiment statistical hypothesis test paired t-test machine learning