Information retrieval system based on hierarchically organized multi-interest Agent

In order to increase the searching accuracy in the huge web resources for the information retrieval system based on Agent, an information retrieval system based on hierarchically organized multi-interest Agent (IRHOMIA) is presented. After making the interest predictions on user's query information, the model will generate weight vectors of user's interest item, then input the vectors to the trained neural network, and compare the given threshold value with each value of the vectors generated by the network's output level. Through the comparison, the searching tasks will assign to the other interest Agent possessing the searching tools of corresponding resources. Through the experiment, it shows that, in the aspects of predicting users' interest, IRHOMIA is more effective than the traditional information retrieval system and the single-interest Agent retrieval system. Moreover, IRHOIA increases the accuracy over 5% in the recommendation of the searching information.