Purpose: This study aims to explore the relationships between different facets of work task and selection and query-related behavior.Design/methodology/approach:An experiment was conducted to explore the issue. The re...Purpose: This study aims to explore the relationships between different facets of work task and selection and query-related behavior.Design/methodology/approach:An experiment was conducted to explore the issue. The researcher recruited 24 participants and assigned six simulated work task situations to each of them. Each experiment lasted around 2 hours and was recorded by the software tool Morae.Findings: Time(frequency) and time(length) are more closely related to user’s selection and query-related behavior compared to the facet ‘process’ of work task. Knowledge level of work task topic, degree of work task difficulty, and subjective work task complexity are significantly correlated with selection and query-related behavior. Work task difficulty and work task complexity are different concepts. Subjective work task complexity, work task difficulty, and knowledge of work task topic are significantly correlated with user’s selection and query-related behavior.Research limitations/implications: The limitations of this study include a small sample size,limited work task situations, and possible spurious relationships. This study has implications in informing task-based information seeking/search/retrieval research and interactive information retrieval(IIR) systems design.Originality/values: Previous studies usually did not touch upon how different facets of work tasks affected interactive activities. Some studies examining task complexity and information behavior were concerned with how work tasks affect users’ behavior at information-seeking level, rather than at information search level. This study makes contribution to interactive information retrieval,task-based information search and retrieval, and personalization of IR.展开更多
Given the importance of web search volume for reflecting tourists'preferences for certain tourism services and destinations,incorporating these data into forecasting models can significantly improve forecasting pe...Given the importance of web search volume for reflecting tourists'preferences for certain tourism services and destinations,incorporating these data into forecasting models can significantly improve forecasting performance.This study enriches the literature on tourism demand forecasting and tourists'search behavior through segmented Baidu search volume data.First,this study divides Baidu search volume data based on volume sources and periods.Then,by analyzing the most relevant keywords in tourism demand in different segments,this study captures the dynamic characteristics of tourist search behavior.Finally,this study adopts a series of econometric and machine learning models to further improve the performance of tourism demand and forecasting.The findings indicate that tourists’search behavior has changed significantly with the prevalence and popularization of 4G technology and suggest that search volume improves forecasting performance,especially search volume on mobile terminals,from 2014M1–2019M12.展开更多
Purpose: This study attempts to investigate how a user's search behavior changes in the exploratory search process in order to understand the characteristics of the user's search behavior and build a behaviora...Purpose: This study attempts to investigate how a user's search behavior changes in the exploratory search process in order to understand the characteristics of the user's search behavior and build a behavioral model.Design/methodology/approach: Forty-two matriculated full-time senior college students with a female-to-male ratio of 1 to 1 who majored in medical science in Jilin University participated in our experiment. The task of the experiment was to search for information about 'the influence of environmental pollution on daily life' in order to write a report about this topic. The research methods include concept map, query log analysis and questionnaire survey.Findings: The results indicate that exploratory search can significantly change the knowledge structure of searchers. As searchers were moving through different stages of the exploratory search process, they experienced cognitive changes, and their search behaviors were characterized by quick browsing, careful browsing and focused searching.Research limitations: The study used only one search topic, and there is no comparision or control group. Although we took search habits, personal thinking habits, personality characteristics and professional background into account, a more detailed study to analyze the effects of these factors on exploratory search behavior is needed in our further research.Practical implications: This study can serve as a reference for other researchers engaged in the same effort to construct the supporting system of exploratory search.Originality/value: Three methods are used to investigate the behavior characteristics during exploratory search.展开更多
A novel heuristic search algorithm called seeker op- timization algorithm （SOA） is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search...A novel heuristic search algorithm called seeker op- timization algorithm （SOA） is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search direction is based on empir- ical gradients by evaluating the response to the position changes, while step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the SOA is evaluated by using a challenging set of typically complex functions in compari- son to differential evolution （DE） and three modified particle swarm optimization （PSO） algorithms. The simulation results show that the performance of the SOA is superior or comparable to that of the other algorithms.展开更多
In taking into full consideration of the technology acceptance model(TAM),this empirical study has made a few assumptions and also has formulated a model for the study on the level of satisfaction of database users. T...In taking into full consideration of the technology acceptance model(TAM),this empirical study has made a few assumptions and also has formulated a model for the study on the level of satisfaction of database users. This research project was conducted by collecting relevant data from library users of five universities. Specifically, it aimed to measure database users' level of satisfaction and tried to find factors affecting these graduate students who are using databases regularly at their university libraries. An analysis of the collected data shows that the level of database users' satisfaction could be directly affected by the database service quality, the easiness of accessing the system and user perceived notion of usefulness of those databases that they use often. This study also found that database users' gender could be a significant factor in their perceived notion of easiness of accessing databases, and also in their perceived notion of satisfaction for their successful information retrieval operations. The frequency of accessing databases by these graduate students has an impact on users' perceived notion of easiness of database access. The users' school classifications could make a significant difference in their perceived notion on the extent of usefulness of a particular database.展开更多
The present paper reports case study results of the risk assessment of transgenic Bt cotton on a non-target pest,cotton aphid,Aphis gossypii.Several types of techniques,i.e.,electrical penetration graph(EPG),light and...The present paper reports case study results of the risk assessment of transgenic Bt cotton on a non-target pest,cotton aphid,Aphis gossypii.Several types of techniques,i.e.,electrical penetration graph(EPG),light and electron microscopy,bioassays and chemical analysis,were applied to investigate physical and chemical leaf factors of 2 transgenic Bt cotton lines(GK12 and GK19)and their pa-rental non-Bt cotton line(Simian3)associated with searching and feeding behaviors of cotton aphids on leaves or leaf extracts of cotton plants.EPG results showed that there were some differences among behaviors of cotton aphids on 2 Bt cotton and 1 non-Bt cotton lines.Cotton aphids performed similarly to leaf surface extracts from 3 cotton lines;and leaf surface chemicals,mainly volatiles and waxes,were almost identical in the components and concentrations among the cotton lines.However,three cotton lines were quite different from each other in the densities of certain kinds of covering trichomes.Therefore,the relationships between the physical characteristics and the searching behaviors of cotton aphids on the three cotton lines were constructed as the regression equations.Glandular trichomes and covering trichomes with 5 branches influenced the cotton aphids'searching behaviors effectively;and other trichomes with other branches affected aphids in varying ways.These results demonstrated that leaf surface physical factors of transgenic Bt cotton lines different from their parental non-Bt line could affect the penetration behaviors of non-target cotton aphids.Cotton aphids penetrate and feed more easily on two Bt cotton lines than on the non-Bt cotton line.展开更多
The existing search engines are lack of the consideration of personalization and display the same search results for different users despite their differences in interesting and purpose.By analyzing user's dynamic...The existing search engines are lack of the consideration of personalization and display the same search results for different users despite their differences in interesting and purpose.By analyzing user's dynamic search behavior,the paper introduces a new method of using a keyword query graph to express user's dynamic search behavior,and uses Bayesian network to construct the prior probability of keyword selection and the migration probability between keywords for each user.To reflect the dynamic changes of the user's preference,the paper introduces non-lineal gradual forgetting collaborative filtering strategy into the personalized search recommendation model.By calculating the similarity between each two users,the model can do the recommendation based on neighbors and be used to construct the personalized search engine.展开更多
In the era of big data,stock markets are closely connected with Internet big data from diverse sources.This paper makes the first attempt to compare the linkage between stock markets and various Internet big data coll...In the era of big data,stock markets are closely connected with Internet big data from diverse sources.This paper makes the first attempt to compare the linkage between stock markets and various Internet big data collected from search engines,public media and social media.To achieve this purpose,a big data-based causality testing framework is proposed with three steps,i.e.,data crawling,data mining and causality testing.Taking the Shanghai Stock Exchange and Shenzhen Stock Exchange as targets for stock markets,web search data,news,and microblogs as samples of Internet big data,some interesting findings can be obtained.1)There is a strong bi-directional,linear and nonlinear Granger causality between stock markets and investors'web search behaviors due to some similar trends and uncertain factors.2)News sentiments from public media have Granger causality with stock markets in a bi-directional linear way,while microblog sentiments from social media have Granger causality with stock markets in a unidirectional linear way,running from stock markets to microblog sentiments.3)News sentiments can explain the changes in stock markets better than microblog sentiments due to their authority.The results of this paper might provide some valuable information for both stock market investors and modelers.展开更多
基金sponsored by National Social Science Foundation of China(Grant No. 11BTQ009)
文摘Purpose: This study aims to explore the relationships between different facets of work task and selection and query-related behavior.Design/methodology/approach:An experiment was conducted to explore the issue. The researcher recruited 24 participants and assigned six simulated work task situations to each of them. Each experiment lasted around 2 hours and was recorded by the software tool Morae.Findings: Time(frequency) and time(length) are more closely related to user’s selection and query-related behavior compared to the facet ‘process’ of work task. Knowledge level of work task topic, degree of work task difficulty, and subjective work task complexity are significantly correlated with selection and query-related behavior. Work task difficulty and work task complexity are different concepts. Subjective work task complexity, work task difficulty, and knowledge of work task topic are significantly correlated with user’s selection and query-related behavior.Research limitations/implications: The limitations of this study include a small sample size,limited work task situations, and possible spurious relationships. This study has implications in informing task-based information seeking/search/retrieval research and interactive information retrieval(IIR) systems design.Originality/values: Previous studies usually did not touch upon how different facets of work tasks affected interactive activities. Some studies examining task complexity and information behavior were concerned with how work tasks affect users’ behavior at information-seeking level, rather than at information search level. This study makes contribution to interactive information retrieval,task-based information search and retrieval, and personalization of IR.
基金partly supported by the National Natural Science Foundation of China under Grant No.72101197by the Fundamental Research Funds for the Central Universities under Grant No.SK2021007.
文摘Given the importance of web search volume for reflecting tourists'preferences for certain tourism services and destinations,incorporating these data into forecasting models can significantly improve forecasting performance.This study enriches the literature on tourism demand forecasting and tourists'search behavior through segmented Baidu search volume data.First,this study divides Baidu search volume data based on volume sources and periods.Then,by analyzing the most relevant keywords in tourism demand in different segments,this study captures the dynamic characteristics of tourist search behavior.Finally,this study adopts a series of econometric and machine learning models to further improve the performance of tourism demand and forecasting.The findings indicate that tourists’search behavior has changed significantly with the prevalence and popularization of 4G technology and suggest that search volume improves forecasting performance,especially search volume on mobile terminals,from 2014M1–2019M12.
基金supported by the National Social Science Foundation(Grant No.:11BTQ045)
文摘Purpose: This study attempts to investigate how a user's search behavior changes in the exploratory search process in order to understand the characteristics of the user's search behavior and build a behavioral model.Design/methodology/approach: Forty-two matriculated full-time senior college students with a female-to-male ratio of 1 to 1 who majored in medical science in Jilin University participated in our experiment. The task of the experiment was to search for information about 'the influence of environmental pollution on daily life' in order to write a report about this topic. The research methods include concept map, query log analysis and questionnaire survey.Findings: The results indicate that exploratory search can significantly change the knowledge structure of searchers. As searchers were moving through different stages of the exploratory search process, they experienced cognitive changes, and their search behaviors were characterized by quick browsing, careful browsing and focused searching.Research limitations: The study used only one search topic, and there is no comparision or control group. Although we took search habits, personal thinking habits, personality characteristics and professional background into account, a more detailed study to analyze the effects of these factors on exploratory search behavior is needed in our further research.Practical implications: This study can serve as a reference for other researchers engaged in the same effort to construct the supporting system of exploratory search.Originality/value: Three methods are used to investigate the behavior characteristics during exploratory search.
基金supported by the National Natural Science Foundation of China(60870004)
文摘A novel heuristic search algorithm called seeker op- timization algorithm （SOA） is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search direction is based on empir- ical gradients by evaluating the response to the position changes, while step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the SOA is evaluated by using a challenging set of typically complex functions in compari- son to differential evolution （DE） and three modified particle swarm optimization （PSO） algorithms. The simulation results show that the performance of the SOA is superior or comparable to that of the other algorithms.
基金supported by the Ministry of Education of China(Grant No.05JZD00024)
文摘In taking into full consideration of the technology acceptance model(TAM),this empirical study has made a few assumptions and also has formulated a model for the study on the level of satisfaction of database users. This research project was conducted by collecting relevant data from library users of five universities. Specifically, it aimed to measure database users' level of satisfaction and tried to find factors affecting these graduate students who are using databases regularly at their university libraries. An analysis of the collected data shows that the level of database users' satisfaction could be directly affected by the database service quality, the easiness of accessing the system and user perceived notion of usefulness of those databases that they use often. This study also found that database users' gender could be a significant factor in their perceived notion of easiness of accessing databases, and also in their perceived notion of satisfaction for their successful information retrieval operations. The frequency of accessing databases by these graduate students has an impact on users' perceived notion of easiness of database access. The users' school classifications could make a significant difference in their perceived notion on the extent of usefulness of a particular database.
基金the National Key Basic Research Program(Grant No.G2000046803)National Natural Science Foundation of China(Grant No.39970153)the Public and Professional Project of Environmental Protection of China(Grant No.200709047)
文摘The present paper reports case study results of the risk assessment of transgenic Bt cotton on a non-target pest,cotton aphid,Aphis gossypii.Several types of techniques,i.e.,electrical penetration graph(EPG),light and electron microscopy,bioassays and chemical analysis,were applied to investigate physical and chemical leaf factors of 2 transgenic Bt cotton lines(GK12 and GK19)and their pa-rental non-Bt cotton line(Simian3)associated with searching and feeding behaviors of cotton aphids on leaves or leaf extracts of cotton plants.EPG results showed that there were some differences among behaviors of cotton aphids on 2 Bt cotton and 1 non-Bt cotton lines.Cotton aphids performed similarly to leaf surface extracts from 3 cotton lines;and leaf surface chemicals,mainly volatiles and waxes,were almost identical in the components and concentrations among the cotton lines.However,three cotton lines were quite different from each other in the densities of certain kinds of covering trichomes.Therefore,the relationships between the physical characteristics and the searching behaviors of cotton aphids on the three cotton lines were constructed as the regression equations.Glandular trichomes and covering trichomes with 5 branches influenced the cotton aphids'searching behaviors effectively;and other trichomes with other branches affected aphids in varying ways.These results demonstrated that leaf surface physical factors of transgenic Bt cotton lines different from their parental non-Bt line could affect the penetration behaviors of non-target cotton aphids.Cotton aphids penetrate and feed more easily on two Bt cotton lines than on the non-Bt cotton line.
基金supported by the National Natural Science Foundation of China(60432010)the National Basic Research Program of China(2007CB307103)+1 种基金the Fundamental Research Funds for the Central Universities(2009RC0507)Important Science&Technology Specific Project of Guizhou Province(【2007】6017)
文摘The existing search engines are lack of the consideration of personalization and display the same search results for different users despite their differences in interesting and purpose.By analyzing user's dynamic search behavior,the paper introduces a new method of using a keyword query graph to express user's dynamic search behavior,and uses Bayesian network to construct the prior probability of keyword selection and the migration probability between keywords for each user.To reflect the dynamic changes of the user's preference,the paper introduces non-lineal gradual forgetting collaborative filtering strategy into the personalized search recommendation model.By calculating the similarity between each two users,the model can do the recommendation based on neighbors and be used to construct the personalized search engine.
基金sponsored by the National Natural Science Foundation of China under Grant Nos.715732447153201371202115 and 71403260。
文摘In the era of big data,stock markets are closely connected with Internet big data from diverse sources.This paper makes the first attempt to compare the linkage between stock markets and various Internet big data collected from search engines,public media and social media.To achieve this purpose,a big data-based causality testing framework is proposed with three steps,i.e.,data crawling,data mining and causality testing.Taking the Shanghai Stock Exchange and Shenzhen Stock Exchange as targets for stock markets,web search data,news,and microblogs as samples of Internet big data,some interesting findings can be obtained.1)There is a strong bi-directional,linear and nonlinear Granger causality between stock markets and investors'web search behaviors due to some similar trends and uncertain factors.2)News sentiments from public media have Granger causality with stock markets in a bi-directional linear way,while microblog sentiments from social media have Granger causality with stock markets in a unidirectional linear way,running from stock markets to microblog sentiments.3)News sentiments can explain the changes in stock markets better than microblog sentiments due to their authority.The results of this paper might provide some valuable information for both stock market investors and modelers.
