Research On Health Information Discovery Technology Based On Spatiotemporal Awareness

The age of the Internet to promote information technology revolution in the field of health makes people not only pay more and more attention on the quality of life of the increasingly high demand but also on the health of individuals and families; besides disease treatment, they also focus on disease prevention and health care. Although modern health awareness is stronger than ever, most people are still a little understanding of the state in healthy diet, disease prevention, and long term monitoring for chronic diseases. Therefore, there is more and more study in the field of health information technology in recent years, and a lot of personal health care management systems and wearable mobile devices occurs, but they are only used for the storage and management of health data other than providing health service for people by employing the correlation among health data.Temporal and spatial information are closely related to our daily life, and we often submit keyword queries with explicit or implicit spatiotemporal information to search engine in usual information search tasks. For example, people often search restaurants near them for the hottest food in latest time in some takeaway websites and so on. As we can imagine, the search results will be very bad without spatiotemporal information in the keyword queries. Nowadays, Internet information has explosive growth, it become more and more difficult to quickly find satisfying information in the massive Internet information, because general search engines can not understand the intention of users well. Therefore, information discovery technologies is derived.Therefore, to solve the problem of lacking spatiotemporal awareness ability in existing information discovery technologies in the field of health, spatiotemporality-aware information discovery technologies and their applications in health care field are studied, and a series of methods are proposed. In this paper, the art of the state in information discovery technologies and spatiotemporal awareness are investigated at home and abroad; existing problems and challenges in the research field are analyzed. Then, a spatiotemporal information discovery model is proposed. Finally, a health information extraction algorithm and spatiotemporality-aware information discovery algorithm(called STAORank) are designed. STAORank algorithm is an improved algorithm based on ObjectRank algorithm, in which spatiotemporal similarity between queries and health data are computed. STAORank algorithm includes the following steps:firstly, node set containing query keywords is produced; secondly, those candidate nodes meeting the time and space constraints are worked out; finally, Top-k results are generated from the candidate results by computing the final scores of candidate results in ranking function and sorting them in heap-sort method.In this paper, a spatiotemporality-aware health information discovery prototype system is implemented and a lot of health data is extracted. P@k and query time measures are used to compare the experimental results from different algorithms. Experimental results show that STAORank algorithm perform effectively.