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IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2013年第4期17卷 853-861页

作者： Hsieh, Sheau-Ling Chang, Wen-Yung Chen, Chi-Huang Weng, Yung-Ching Natl Chiao Tung Univ Hsinchu 30010 Taiwan Natl Chiao Tung Univ Coll Comp Sci Hsinchu 30010 Taiwan Natl Taiwan Univ Dept Elect Engn Taipei 10617 Taiwan Natl Taiwan Univ Hosp Informat Off Taipei 100 Taiwan

Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis;dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705;MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496;MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database.

关键词： Semantic similarity support vector machine page-count-based corpus-based web search engine

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Development of a Novel Compressed Index-Query web search engine Model

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY AND web engineERING 2011年第3期6卷 39-56页

作者： Al-Bahadili, Hussein Al-Saab, Saif Petra Univ Amman Jordan Univ Banking & Financial Sci Amman Jordan

In this paper, the authors present a description of a new web search engine model, the compressed index-query (CIQ) web search engine model. This model incorporates two bit-level compression layers implemented at the back-end processor (server) side, one layer resides after the indexer acting as a second compression layer to generate a double compressed index (index compressor), and the second layer resides after the query parser for query compression (query compressor) to enable bit-level compressed index-query search. The data compression algorithm used in this model is the Hamming codes-based data compression (HCDC) algorithm, which is an asymmetric, lossless, bit-level algorithm permits CIQ search. The different components of the new web model are implemented in a prototype CIQ test tool (CIQTT), which is used as a test bench to validate the accuracy and integrity of the retrieved data and evaluate the performance of the proposed model. The test results demonstrate that the proposed CIQ model reduces disk space requirements and searching time by more than 24%, and attains a 100% agreement when compared with an uncompressed model.

关键词： Bit-Level Compression Full-Text Compressed Self-Index Hamming Codes-Based Data Compression (HCDC) Algorithm Indexes Query Optimization web search engine

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Simulating urban growth in a metropolitan area based on weighted urban flows by using web search engine

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INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2015年第10期29卷 1721-1736页

作者： Lin, Jinyao Li, Xia Sun Yat Sen Univ Sch Geog & Planning Guangzhou 510275 Guangdong Peoples R China Sun Yat Sen Univ Guangdong Key Lab Urbanizat & Geosimulat Guangzhou 510275 Guangdong Peoples R China

As a consequence of rapid and immoderate urbanization, simulating urban growth in metropolitan areas effectively becomes a crucial and yet difficult task. Cellular automata (CA) model is an attractive tool for understanding complex geographical phenomena. Although intercity urban flows, the key factors in metropolitan development, have already been taken into consideration in CA models, there is still room for improvement because the influences of urban flows may not necessarily follow the distance decay relationship and may change over time. A feasible solution is to define the weights of intercity urban flows. Therefore, this study presents a novel method based on weighted urban flows (CA(WeightedFlow)) with the support of web search engine. The relatedness measured by the co-occurrences of the cities names (toponyms) on massive web pages can be deemed as the weights of intercity urban flows. After applying the weights, the gravitational field model is integrated with Logistic-CA to fulfill the modeling task. This method is employed to the urban growth simulation in the Pearl River Delta, one of the most urbanized metropolitan areas in China, from 2005 to 2008. The results indicate that our method outperforms traditional methods with respect to two measures of calibration goodness-of-fit. For example, CA(WeightedFlow) can yield the best value of 'figure of merit'. Moreover, the proposed method can be further used to explore various development possibilities by simply changing the weights.

关键词： cellular automata web search engine weighted urban flow gravitational field model calibration

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Specialized design of web search engine for the blind people

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4th International Conference on Universal Access in Human-Computer Interaction held at the HCI International 2007

作者： Yang, Yi-Fan Hwang, Sheue-Ling Taipei Res Ctr HTC Taipei Taiwan Natl Tsing Hua Univ Dept Ind Engn & Engn Mgmt Hsinchu Taiwan

ISBN: (纸本)9783540732822

In this research, Google website was taken as a web prototype to get modified. Specialized search engine for the Blind (SSEB) was constructed with an accessible interface and some improved functions (i.e., searching assistance functions, user-centered functions, and specialized design for the blind). An experiment was conducted to verify the effect of SSEB. From experimental results, it's significant that users attained better performance in SSEB than in Google. Users also showed higher satisfaction with SSEB. This research proves that the consideration for designing an accessible website for the blind users is very important. It is expected that the users group of SSEB can be expanded to all visual-impaired people in the future. So that all people can keep pace with the changing World Wide web, and make good use of all the Internet resources without disabilities and limitations.

关键词： web search engine blind web searching web accessibility google

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The webengine - A Fully Integrated, Decentralised web search engine 18

The WebEngine - A Fully Integrated, Decentralised Web Search...

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2nd International Conference on Natural Language Processing and Information Retrieval (NLPIR)

作者： Kubek, Mario M. Unger, Herwig Univ Hagen Chair Commun Networks Univ Str 27 Hagen Germany

ISBN: (纸本)9781450365512

This paper presents a basic, new concept for decentralised web search which addresses major shortcomings of current web search engines. Its methods are characterised by their local working principles, making it possible to employ them on diverse hardware configurations. The concept's implementation in form of an interactive, librarian-inspired peer to -peer software client, called 'webengine', is elaborated on in detail. This software extends and interconnects common web servers creating and forming a decentralised web search system on top of the existing web structure while for the first time combining modern text analysis techniques with novel and efficient search functions as well as approaches for the semantically induced P2P-network construction and its flexible management. This way, an alternative, fully integrated and powerful web search engine under the motto `The web is its own search engine.' is built making the web searchable without any central authority.

关键词： webengine web search engine P2P-system co-occurrence graph librarian of the web

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search engine Pictures: Empirical Analysis of a web search engine Query Log 3

Search Engine Pictures: Empirical Analysis of a Web Search E...

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3rd International Conference on web Research (ICWR)

作者： Shoeleh, Farzaneh Zahedi, Mohammad Sadegh Farhoodi, Mojgan Iran Telecommun Res Ctr Tehran Iran

ISBN: (纸本)9781538604205

Since the use of internet has incredibly increased, it becomes an important source of knowledge about anything for everyone. Therefore, the role of search engine as an effective approach to find information is critical for internet's users. The study of search engine users' behavior has attracted considerable research attention. These studies are helpful in developing more effective search engine and are useful in three points of view: for users at the personal level, for search engine vendors at the business level, and for government and marketing at social society level. These kinds of studies can be done through analyzing the log file of search engine wherein the interactions between search engine and the users are captured. In this paper, we aim to present analyses on the query log of a well-known and most used Persian search engine. Our analyses are presented in three main categories: 1) Stats-based analyses, 2) Temporal-based analyses, and 3) Topic-based analyses. The obtained results are promising. Mobile users often posted queries in weekends, whereas web users utilize the search engine in workweeks. The majority of queries posted form most-populated cities. Additionally, Iranians are mostly interested in political, social, and economical topics.

关键词： web search engine Query Log analyses Information search and Retrival

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PERSONALIZED IMAGE RECOMMENDATION FOR web search engine USERS

PERSONALIZED IMAGE RECOMMENDATION FOR WEB SEARCH ENGINE USER...

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Li, Yuncheng Luo, Jiebo Mei, Tao Univ Rochester Dept Comp Sci Rochester NY 14627 USA Microsoft Res Beijing Peoples R China

ISBN: (纸本)9781479947614

We introduce and investigate a novel problem of image recommendation for web search engine users. Modern web search engines have become a critical assistant for people's daily life. Through interacting with web search engines, users exhibit personalized information needs in various aspects. While this information is critical to improve user experience, it is mostly used only in the web search domain. In this paper, we propose to leverage web search engine users' behavior data to perform image recommendation. To this end, we have developed a two-stage method to label users' preferences for images through crowdsourcing techniques. The two-stage annotation consists of 1) inferring a user's general interests and 2) estimating if this user will be interested in an image. In addition, we implement a baseline algorithm to demonstrate the promise of the proposed cross-domain recommendation framework.

关键词： cross-media recommendation user preference web search engine

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Enriching Arabic Tweets Representation based on web search engine and the Rough Set Theory

Enriching Arabic Tweets Representation based on Web Search E...

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IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

作者： Bekkali, Mohammed Sahmoudi, Issam Lachkar, Abdelmonaime USMBA ENSA Dept Elect & Comp Engn Fes Morocco

ISBN: (纸本)9781450338547

Twitter is a popular micro-blogging service where users search for timely and social information. Users post short text messages called Tweets, which are limited in length. These Tweets are different from traditional documents in its shortness and sparseness. As a result, short text tends to be ambiguous without enough contextual information. To address these issues, we propose an efficient method to enrich the tweet's representation for the Arabic language using web search engine as a large and open corpus and the Rough Set Theory which is a mathematical tool to deal with vagueness and uncertainty. To assess the performance of the proposed system, a series of experiments has been conducted. The effectiveness of our system has been evaluated and compared in terms of the F1-measure using the Naive Bayesian (NB) and the Support Vector Machine (SVM) classifiers in our Arabic Tweets Categorization System. The obtained results show that enriching the tweet's representation increases significantly the F1-measure of the Arabic tweets categorization system.

关键词： Twitter Short Text Arabic Tweets Rough Set Theory web search engine Snippets

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32nd Annual International Conference of the IEEE engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Chen, Chi-Huang Hsieh, Sheau-Ling Weng, Yung-Ching Chang, Wen-Yung Lai, Feipei Natl Taiwan Univ Dept Elect Engn 1Sec 4Roosevelt Rd Taipei 10617 Taiwan Natl Chiao Tung Univ IT Ctr EECS Intl Grad Program Inst Hsinchu Taiwan Natl Taiwan Univ Dept Comp Sci & Engn Taipei Taiwan Natl Chiao Tung Univ Inst Comp Sci & Engn Hsinchu 30050 Taiwan Natl Taiwan Univ Grad Inst Biomed Elect & Bioinformat Taipei Taiwan

ISBN: (纸本)9781424441242

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the web search engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

关键词： Internet web search engine biomedical domains correlation coefficients information retrieval lexico-syntactic patterns medical information systems natural language processing natural language processing page counts page-count-based semantic similarity search engines semantic web semantic networks similarity scores support vector machines support vector machines

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Analysis of spatial patterns of public attention on housing prices in Chinese cities: A web search engine approach

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APPLIED GEOGRAPHY 2016年 70卷 68-81页

作者： Zhang, Zuo Tang, Wenwu Hubei Univ Sch Business Youyi Rd Wuhan 430062 Peoples R China Univ N Carolina Dept Geog & Earth Sci Charlotte NC 28223 USA Univ N Carolina Ctr Appl GISci Charlotte NC 28223 USA

Housing price has become one of the most pressing issues facing urban residents in China in recent years and received considerable attention. However, detailed housing price data are often ill-documented or unavailable for the public, thus posing a grand challenge for the study of housing prices in China. Because individuals' Internet search activities can be recorded by web search engines, the analysis of these web search activities in cyber-space may provide a means of better understanding public attention and associated concerns in real geographic space. In this study, we focus on exploring the spatial patterns of public attention on housing price through the analysis of web query activities based on Baidu Index, a Chinese keyword analysis tool from Baidu web search engine. We propose a new index based on keyword query outcome from Baidu search database to analyze spatially heterogeneous patterns of housing price attention from 19 large and medium-sized cities in China. We evaluate the spatial network structure of housing price attention, and develop a new index to measure the intensity of interaction relationships among cities of interest. Our results show that spatial interactions of housing price attention between cities evaluated using the new method are consistent with those from a gravity model. Meanwhile, as revealed from Baidu Index-based indicators, strong spatial association patterns exist among cities that form urban agglomerations. Further, our results demonstrate that the web search engine approach, based on the coupling of cyber-space and geographic space, provides solid support for the study of housing price attention and its spatially explicit patterns in China. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Urban study Housing price Baidu Index Spatial structure web search engine

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