Predictions of Citations of a Scholarly Paper

Bibliometrics is a statistical analysis of written publications such as books or articles. A bibliographic citationis a reference to a book, article, web page, or other published item. Thus citations are useful for identifying the progress ofthe particular work and measuring the quality of the research article. The cited papers are downloaded using the crawler. Fromthe downloaded article, identify article relation by analyzing the citation context of the article. So first extract the citation context from the article. Citation context are classifies based on cue phrases of Simon tufel. Next, identify the relation of unlabeled article by word embedding. After labeling all articles identifythe perspective behind the citation of the article. In this project, citation relation is identified based on cue phrases of Simon tufel finally article impact is quantified based on the citation network formed from citation analysis. Index Terms: bibliometrics, citation, word embedding, article

Discovering relationships from imperial court documents of Qing China

The Qing Imperial Court documents are a major source of primary research material for studying the Qing era China since they provide the most direct and first-hand details of how national affairs were handled. However, the way Qing archived these documents has made it cumbersome to collect documents covering the same event and rebuild their original contexts. In this paper, we describe some information technology that we have developed to discover two important and useful relations among these documents. The first is the citation relation among the Imperial Edicts and the Memorials. We discovered 6,801 pairs from the 37,831 Taiwan-related Imperial Court documents in the Taiwan History Digital Library (THDL) and produced 1,101 graphs of successive citations, which we call IE-M diagrams. The second relation is a template relation, which indicates groups of documents that were created following a specific format. Numerical data can also be tabulated from these documents and be used for further analysis. Our studies show how information technology can be used to discover useful contexts from seemingly unrelated historical documents.

A Hybrid Method Based on HITS for Literature Recommendation

In this paper we propose a hybrid method of literature recommendation in the academic community. First, we refer the objective recommendation based on HITS algorithm by constructing a directed graph according to the literature citation relation and then select the articles considering the authority and hub score of each article synthetically and add them to the recommendation list. This can narrow the recommendation scope and give a more authoritive recommendation. Second, the subjective recommendation is based on collaborative filtering by comparing the ratings of other similar users for the objects in recommendation list. The difference is we discover the similar user by clustering them. And the experiment shows the method can provide better recommendation results and is timesaving.