A Novel Information Search and Recommendation Services Platform Based on an Indexing Network (Short Paper)

With the rapid development of Internet technology, information resources on the Internet become more abundant, but also bring some problems like diversity, heterogeneity, disorder, and redundancy. Given a brief expression like search keywords only, users' needs are ambiguous. Therefore, current technologies of search applications relying on direct keyword matching cannot meet the requirements of users exactly. Service applications are hoped to be more intelligent and knowledgeable. To solve such challenge, this paper attempts to organize web pages into a semantic association graph based on a novel model - indexing network, which can provide more valuable information and services for users. An information search and recommendation services platform is implemented using cloud distributed systems (Hadoop + Habse + Zookeeper) based on Sugon-Tongji cloud platform that is located at Tongji University. 70 million web pages are crawled on the Internet and their corresponding indexing network model are constructed. Several novel services are implemented and provided on the platform, such as search location, search navigation, category/keyword recommendation, and the interaction interface of the indexing network. System demonstration and experimental analysis show that the proposed platform can provide and support more knowledgeable and valuable information search-related services, thereby better meeting the growing needs of Internet users.