دانلود مقاله ISI انگلیسی شماره 157351
ترجمه فارسی عنوان مقاله

استخراج هوش تکنولوژی از اختراعات: تجزیه و تحلیل معنایی مبتنی بر پیش فرض

عنوان انگلیسی
Deriving technology intelligence from patents: Preposition-based semantic analysis
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
157351 2018 20 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Informetrics, Volume 12, Issue 1, February 2018, Pages 217-236

ترجمه کلمات کلیدی
فناوری اطلاعات، جستجوی فناوری، روند تکنولوژی، تجزیه و تحلیل ثبت اختراع، معنایی حرف اضافه، استخراج متن، کلید واژه ها، استخراج متن،
کلمات کلیدی انگلیسی
Technology intelligence; Technology search; Technology trends; Patent analysis; Semantic; Preposition; Text mining; Key-words; Text mining;
پیش نمایش مقاله
پیش نمایش مقاله  استخراج هوش تکنولوژی از اختراعات: تجزیه و تحلیل معنایی مبتنی بر پیش فرض

چکیده انگلیسی

Patents are one of the most reliable sources of technology intelligence, and the true value of patent analysis stems from its capability of describing the content of technology based on the relationships between keywords. To date a number of techniques for analyzing the information contained in patent documents that focus on the relationships between keywords have been suggested. However, a drawback of the existing keyword approaches is that they cannot yet determine the types of relationships between the keywords. This study proposes a novel approach based on preposition semantic analysis network which overcomes the limitations of the existing keywords-based network analysis and demonstrates its potential through an application. A preposition is a word that defines the relationship between two neighboring words, and, in the case of patents, prepositions aid in revealing the relationships between keywords related to technologies. To demonstrate the approach, patents regarding an electric vehicle were employed. 13 prepositions were identified which could be used to define 5 relationships between neighboring technological terms: “inclusion (utilization),” “objective (purpose),” “effect,” “process,” and “likeness.” The proposed approach is expected to improve the usability of keyword-based patent analyses and support more elaborate studies on patent documents.