Neural Network Modelling of the Information Behavior of Database Users Based on their Previous Interactions with the Search Results

In designing search engines, it is important to check the database you are studying and make a connection with it.This study is an applied one conducted by using observation method. What is used in this study is a case study.The pattern of most searches is generally partial and specific in most cases. Participants begin their search with general information such as introducing and reviewing facts, and then focusing on specific aspects. In some cases, users come up with new ideas while searching. According to the results, general background, subject knowledge, time range and tools available influence desired response.According to the analysis of findings and results, it is suggested that information behavior using neural network is more accurate in identifying information skills, barriers, goals and motivation and determining and predicting resources and services. Information and ways of accessing information should be compared with the results of present study. Based on the results, it seems that specialized information retrieval training for all classes of users is needed to increase information skills of current and future users.Current search engines retrieve only part of relevant documents in a collection. Better models are needed to overcome the huge volume of documents. The proposed model in this way enables improved data retrieval in a short period of time. It is also possible that search model is also updated each time with user searches and results in more accurate results.