{"title":"The relationship between user preferences in interactive information retrieval evaluation","authors":"Tanisha Gahlawat, P. Bhatia, D. Mehrotra","doi":"10.1109/ICRITO.2017.8342463","DOIUrl":null,"url":null,"abstract":"The paper investigates various factors (System Reliability, User Efficacy, User behavior and User cognitive skills) that affect a user while retrieving information. These factors can be used to improve the efficiency of the system. In this research, we have created a model improving the classical IR model. The factors that affect the user are clubbed together to form a User Characteristic Data (UCD). The system interacts with the UCD to obtain the results as per the user query. The model takes in user's relevance feedback to update the UCD. The objective here is to retrieve better results every time the user wants some information. Therefore, the IIR models should consider these factors while evaluating the documents for the query given by the user for his information need.","PeriodicalId":357118,"journal":{"name":"2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRITO.2017.8342463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper investigates various factors (System Reliability, User Efficacy, User behavior and User cognitive skills) that affect a user while retrieving information. These factors can be used to improve the efficiency of the system. In this research, we have created a model improving the classical IR model. The factors that affect the user are clubbed together to form a User Characteristic Data (UCD). The system interacts with the UCD to obtain the results as per the user query. The model takes in user's relevance feedback to update the UCD. The objective here is to retrieve better results every time the user wants some information. Therefore, the IIR models should consider these factors while evaluating the documents for the query given by the user for his information need.