Papers by Keyword: Information Retrieval

Abstract: Energy efficiency of production systems and of the product itself has grown to a critical competitive factor. Besides the manufacturer’s monetary motivation there are increasing incentives to meet customers’ expectations regarding lifecycle cost and the ecological footprint of products. That neo-ecology, as one megatrend, leads to a new business moral resulting in an energy optimization of the whole product life cycle in terms of resource and energy input. There is a plenty of measures to reduce the energy consumption of a production system and thus to increase its efficiency. To do so companies do not have to develop proprietary solutions for their production sites but can draw on a large pool of measures. However, in practice, many energy optimization measures are unknown to their energy managers. This is mainly owing to the fact that there is no standardized categorization for energy optimization potentials yet. In addition, many efficiency deficits remain undetected as a result of a non-existing efficient methodology for finding energy consumption optimization measures. The domain of information retrieval addresses this issue, as it is able to provide documents matching the user’s information demand. Nevertheless, search queries have to be sufficiently well known in order to gain adequate results. In this paper we show how ontologies can be used to support the user in defining search queries and finding optimization measures efficiently. As formal and explicit specifications of shared conceptualizations, ontologies offer the possibility to represent relevant parts of knowledge in a standardized, machine-readable manner. Therefore, ontologies improve upon data models, which are mainly used for single applications. For the purpose of energy efficiency in production environments, we provide both a methodology to build ontologies for describing energy saving measures and illustrate the application for explicit energy efficiency optimization measures.

Abstract: The top-ranked documents from various information sources that are merged together into a unified ranked list may cover the same piece of relevant information, and cannot satisfy different user needs. Result diversification(RD) solves this problem by diversifying results to cover more information needs. In recent times, RD has attracted much attention as a means of increasing user satisfaction in general purpose search engines. A myriad of approaches have been proposed in the related works for the diversification problem. However, no concrete study of search result diversification has been done in a Distributed Information Retrieval(DIR) setting. In this paper, we survey, classify and propose a theoretical framework that aims at improving diversification at the result merging phase of a DIR environment.

Abstract: We propose a film retrieval method based on ontology. This method can realize automatically recommendation when users query film resources, even though not giving search keywords explicitly. In this paper, we represent the film retrieval method and film ontology model. And then we define several inference rules and give an example to illustrate the reasoning process. Furthermore, it is discussed how to recommend related films. The film retrieval method based on ontology can do benefit to search film resources intelligently and easily.

Abstract: The intelligent information retrieval model based on multi-agent imitates and synthesizes the features of search engine and information retrieval in the website. It realizes high recall-precision and high precision of the retrieval effectively, and has good flexibility and expansibility. It is convenient for users to configure and choose target source of retrieval.

Abstract: This paper is based on the study of typical strategy of water bloom governance in China and introduces information retrieval method in water bloom governance. It can both ensure accuracy of the search and improve the search speed to combine decision tree and CPN neural network as retrieval mechanism. Finally it can be proved that the information retrieval mechanism is effective in governance decision of water bloom after using the Beihai in Beijing as the example.

Abstract: With the Computer Integrated Manufacturing System and Information Technology rapid development, rapid retrieval multilingual becomes one of the hot spots in Machine Translation. The cross-language information retrieval (CLIR) provides a convenient way, enabling users to use their own familiar language to submit queries to retrieve documents in another language. Basic query expansion is one of the effective methods to improve recall of information retrieval. There are many researchers have proposed many extension methods, but most methods are simply added to the query expansion terms. If we do not distinguish the original query words and extended words, expanded query may deviate from the original semantics. So, it is very inconvenience for mechanical engineer and programmer. Based on Dempster-Shafer theory of evidence, we proposed a query expansion computing model, which considered as the main evidence of the original query terms, while the extensions as a secondary evidence of the original query terms. Which method to use semantic dictionary Han and Uygur-Chinese bilingual dictionary of synonyms forest and How to get the query word synonyms, near-synonyms and hypernym. Latent Semantic Analysis is used to obtain semantic relationships query words related words the using potentially large-scale text. The combination of these two types of evidence is in order to put forward a weighted combination of the Dempster-Shafer rule. Experimental results show that this method can effectively improve retrieval efficiency in Mechanical Engineering and Information Technology. The research results can be provided a reference for CIMS multilingual quick retrieval.

Abstract: The process of building the database of tilapia’s farming and breeding is described in this paper. It presents the conversion between the database and the extra data files. It describes several strategies to achieve the data constraints of this database and presents the information retrieval methods based on this database. It described commonly used data analysis algorithms, and comes up with some solutions to solve the problem that reading the database frequently makes the efficiency of algorithm slow. Finally, it briefly describes some measures of maintaining the security of the database.

Abstract: With the rapid development of Internet, more and more information has been displayed to people. More and more researcher pay more attention to how to find useful information from this huge information ocean. We design the topic-oriented information retrieval system in order to overcome the drawback of generic crawler. The system retrieves topic information efficiently and helps user get useful information rapidly and exactly.

Abstract: XML is a new standard for data representation and exchange, which has been widely used on the Internet. XML retrieval has caused more and more researchers concern. How to improve the retrieval efficiency has become an important study field, this paper proposes the retrieval method based on keyword weight and structure extension, which can get the middle retrieval results in accordance with calculating the keyword weight, and further to retrieval by implementing structural extension of middle retrieval results, then can get the final query results. The experiment results show that the retrieval method has high accuracy and the recall rate compared with the traditional retrieval method.

Abstract: Web search engine based on DNS, the standard proposed solution of IETF for public web search system, is introduced in this paper. Now no web search engine can cover more than 60 percent of all the pages on Internet. The update interval of most pages database is almost one month. This condition hasn't changed for many years. Converge and recency problems have become the bottleneck problem of current web search engine. To solve these problems, a new system, search engine based on DNS is proposed in this paper. This system adopts the hierarchical distributed architecture like DNS, which is different from any current commercial search engine. In theory, this system can cover all the web pages on Internet. Its update interval could even be one day. The original idea, detailed content and implementation of this system all are introduced in this paper.