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literature infrastructure was obtained using bibliometrics and literature of the co-keyword network was visualized. It show how co-word analysis techniques can be used to study R&D in enterprises. The results of the study can help support strategic decision-making on the direction of S&T programs in enterprises.
profiles five kinds of academic resources from four features including resource type, disciplinary distribution, keyword distribution and LDA topic distribution. After fusing user behaviors and resource profiles, the users' preferences are modeled. Finally, the top-N recommendation is made according to user's interest value
in Chinese famous CNKI database, then defined the high frequency keywords and their changes. The result indicated that 'OO', 'Modeling', 'Use case', 'Class diagram', 'Software engineering', 'Software architecture', 'XML' and so forth, are the high frequency words that gain the most attention. And concerns have increased
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.