Subjects: Library Science，Information Science >> Library Science submitted time 2024-04-18
Abstract： Purpose/Significance With the development of the data-driven era and the rise of data-intensive research paradigm, data has become a key element in science and technology decision-making, scientific research management, and research innovation activities. Method/Process This paper introduces the concept of demand-side management, constructs a data service demand model based on users, analyzes the data service needs of different users, explores the construction of a dual flow collaborative service framework system between user needs and data services, introduces ecosystems and related development theories to build a data service ecosystem, and analyzes the relationship between users, subject librarians, data, technology, and the environment. Result/Conclusion On the basis of data service practice and exploration, the idea of constructing data service system was proposed to provide reference for providing accurate and efficient data services in the era of big data, and promoting the sustainable development of data services.
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Awaiting Review
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： When Abstract: ng Chinese texts, the traditional TextRank algorithm only considers the similarity between nodes and neglects other important information of the text. Firstly, aiming at Chinese single document, on the basis of existing research, this paper uses TextRank algorithm, on the one hand, it considers the similarities between sentences, on the other hand, TextRank is combined with the overall structural information of texts and the contextual information of sentences, such as the physical position of the document sentences or paragraph, feature sentences, core sentences and other sentences that may increase the weight of the sentence, all are used to generate the digest candidate sentence group of the text. And then, removing high-similarity sentences by redundancy processing technology on the digest candidate sentence group. Finally, the experimental verification shows that the algorithm can improve the accuracy of the generated digest, indicating the effectiveness of the algorithm.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： How to identify new words quickly and efficiently is a very important task in natural language processing. Aiming at the problems existing in the discovery of new words, there is an algorithm for word-finding new words verbatim from left to right in the uncut word Weibo corpus. One way to get a candidate new word is by computing the candidate word and its right adjacent word mutual information to expand word by word; There are some ways to filter candidate new words to get new word sets. The included methods include calculating the branch entropy, deleting stop words contained in the first or last word of each candidate new word and deleting old words included in the candidate new word set. It solves the problem that some new words can not be recognized due to the mistakes in the word segmentation and It also solves the problem that the large number of repetitive word strings and rubbish words strings generated by the n-gram method are identified as new words. Finally, experiments verified the effectiveness of the algorithm.
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