كليدواژه :
الگوهاي مكرّر , قرآن كريم , داده‌كاوي , متنكاوي , قوانين انجمني
چكيده فارسي :
متن قرآن خصوصيات منحصر به فردي از نظر معنا، مفهوم و موضوع نسبت با ساير متون دارد. كشف الگوهاي پنهان و ارزشمند از درون حجم وسيعي از داده‌هاي خام، به‌تازگي توجه بسياري از پژوهش‌گران را به خود جلب كرده است. متنكاوي زمينه‌اي براي كشف اطلاعات از متون است كه ما را در نيل به اين هدف مي‌تواند كمك كند. در سال‌هاي اخير متنكاوي روي قرآن و كشف دانش نهفته از واژه‌هاي آن، چندي است كه مورد توجه بسياري از متخصصان قرار گرفته است. در اين مقاله با در‌نظر‌گرفتن 6348 آيه قرآن، هر آيه به‌صورت يك سبد خريد در نظر گرفته شده و كلمات هر آيه به‌عنوان اقلام هستند؛ سپس با استفاده از قوانين انجمني، كلمات و آيات قرآن بررسي شده و از ميان 54226 قانون انجمني استخراج‌شده از واژه‌هاي قرآن كه با استفاده از معيارهايي مانند ضريب اطمينان، ضريب پشتيبان، معيارLift و معيار Co-efficient ارزيابي شده‌اند، ده قانون برتر هر معيار تحليل و بررسي شده و بدين ترتيب الگوهاي استخراج‌شده از قوانين انجمني، الگوهاي پرتكرار يك‌تايي، دوتايي و سه‌تايي در قرآن به دست مي‌آيد
چكيده لاتين :
Quran’s Text differs from any other texts in terms of its exceptional concepts, ideas and subjects. To recognize the valuable implicit patterns through a vast amount of data has lately captured the attention of so many researchers. Text Mining provides the grounds to extract information from texts and it can help us reach our objective in this regard. In recent years, Text Mining on Quran and extracting implicit knowledge from Quranic words have been the object of researchers’ focus. It is common that in Quranic experts’ arguments, different sides of the discussion present different intellectual, logical and some non-integrated minor evidence in order to prove their own theories. More often than not, every side of these arguments disapproves of the other’s hypothesis and in the end it is impossible for them to reach a state of consensus on the matter, the reason is that, they do not have a common basis for their arguments and they do not make use of scientific, logical methods to strongly support their theories. Therefore, using modern technological trends regarding Quranic arguments could lead to resolving so many of current discrepancies, caused by human errors, which exist among Quranic researchers. It can help providing a common ground for their arguments in order to reach a comprehensive understanding.
The method used in this research implements frequent pattern mining algorithms, singular frequent patterns as well as dual and tripe frequent patterns in order to analyze Quranic text, in addition to this, Association rules have also been evaluated in the research.
Out of 54226 extracted association rules for Quranic words which have been evaluated by the use of criteria such as confidence coefficient, support coefficient, lift criteria as well as Co-efficient criteria. Top 10 rules for each criterion have been analyzed and reviewed throughout the project.
