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متن کامل


اطلاعات دوره: 
  • سال: 

    1387
  • دوره: 

    14
تعامل: 
  • بازدید: 

    1522
  • دانلود: 

    687
چکیده: 

در دو دهه قبل توانایی های فنی بشر برای تولید و جمع آوری داده ها به سرعت افزایش یافته است. بطور کلی استفاده همگانی از وب و اینترنت ما را مواجه با حجم زیادی از داده و اطلاعات می کند. این رشد انفجاری در داده های ذخیره شده، نیاز مبرم وجود تکنولوژی های جدید و ابزارهای خودکاری را ایجاد کرده که به انسان یاری رسانند تا این حجم زیاد داده را به اطلاعات و دانش تبدیل کند. داده کاوی به عنوان یک راه حل برای این مسائل مطرح می باشد. داده کاوی را می توان عمل استخراج اطلاعات پنهان در یک پایگاه داده بزرگ تعریف کرد. داده کاوی به تحلیلگران برای پیدا کردن الگوها و روابط بین داده ها کمک می کند. یکی از مهمترین زمینه های داده کاوی کشف قوانین وابستگی یا Association Rules mining می باشد که هدف از آن یافتن قوانین الگوهای پنهان در بین حجم زیادی از داده ها است. همچنین چگونگی کاوش در بین داده هایی که حاوی اطلاعات زمانی هستند به عنوان یک مساله مهم در امر داده کاوی مطرح است. از آن جایی که بعضی از اقلام داده در کل پایگاه داده به وفور تکرار نمی شوند، در صورتی که در یک بازه زمانی دارای درجه پشتیبانی (support) بالایی هستند،Temporal Association Rules mining به کشف قوانین موجود در یک بازه زمانی در پایگاه داده می پردازند. یکی از مسائل مهم در زمینه کاوش در داده های زمانی چگونگی تقسیم بندی داده ها به بازه های زمانی می باشد. در این مقاله با ارائه روشی که از الگوی تقویمی برای مشخص کردن بازه های زمانی استفاده می کند و ترکیب آن با روشی که از گراف رابطه بین اجزای پایگاه داده استفاده می کند به استخراج قوانین موجود در این بازه های زمانی پرداخته می شود.

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 1522

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resourcesدانلود 687
اطلاعات دوره: 
  • سال: 

    2016
  • دوره: 

    8
تعامل: 
  • بازدید: 

    149
  • دانلود: 

    0
چکیده: 

TODAY, DEVELOPMENT OF INTERNET CAUSES A FAST GROWTH OF INTERNET SHOPS AND RETAILERS AND MAKES THEM AS A MAIN MARKETING CHANNEL. THIS KIND OF MARKETING GENERATES A NUMEROUS TRANSACTION AND DATA WHICH ARE POTENTIALLY VALUABLE. USING DATA MINING IS AN ALTERNATIVE TO DISCOVER FREQUENT PATTERNS AND Association RuleS FROM DATASETS. IN THIS PAPER, WE USE DATA MINING TECHNIQUES FOR DISCOVERING FREQUENT CUSTOMERS’ BUYING PATTERNS FROM A CUSTOMER RELATIONSHIP MANAGEMENT DATABASE. THERE ARE LOTS OF ALGORITHMS FOR THIS PURPOSE, SUCH AS APRIORI AND FP-GROWTH. HOWEVER, THEY MAY NOT HAVE EFFICIENT PERFORMANCE WHEN THE DATA IS BIG, THEREFORE VARIOUS META-HEURISTIC METHODS CAN BE AN ALTERNATIVE. IN THIS PAPER WE FIRST EXCERPT LOYAL CUSTOMERS BY USING RFM CRITERION TO FACE MORE RELIABLE ANSWERS AND CREATE RELEVANT DATASET. THEN Association RuleS ARE DISCOVERED USING PROPOSED GENETIC ALGORITHM. THE RESULTS SHOWED THAT OUR PROPOSED APPROACH IS MORE EFFICIENT AND HAVE SOME DISTINCTION IN COMPARE WITH OTHER METHODS MENTIONED IN THIS RESEARCH.

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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نویسندگان: 

AFZALI GOLNAR ASSADAT | MOHAMMADI SHAHRIAR

اطلاعات دوره: 
  • سال: 

    2016
  • دوره: 

    4
  • شماره: 

    2
  • صفحات: 

    70-77
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    564
  • دانلود: 

    0
چکیده: 

Data repositories contain sensitive information which must be protected from unauthorized access. Existing data mining techniques can be considered as a privacy threat to sensitive data. Association Rule mining is one of the utmost data mining techniques which tries to cover relationships between seemingly unrelated data in a data base.. Association Rule hiding is a research area in privacy preserving data mining (PPDM) which addresses a solution for hiding sensitive Rules within the data problem. Many researches have be done in this area, but most of them focus on reducing undesired side effect of deleting sensitive Association Rules in static databases. However, in the age of big data, we confront with dynamic data bases with new data entrance at any time. So, most of existing techniques would not be practical and must be updated in order to be appropriate for these huge volume data bases. In this paper, data anonymization technique is used for Association Rule hiding, while parallelization and scalability features are also embedded in the proposed model, in order to speed up big data mining process. In this way, instead of removing some instances of an existing important Association Rule, generalization is used to anonymize items in appropriate level. So, if necessary, we can update important Association Rules based on the new data entrances. We have conducted some experiments using three datasets in order to evaluate performance of the proposed model in comparison with Max-Min2 and HSCRIL. Experimental results show that the information loss of the proposed model is less than existing researches in this area and this model can be executed in a parallel manner for less execution time.

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 564

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مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
نویسندگان: 

LAMMA E. | RIGUZZI F. | STORARI S.

اطلاعات دوره: 
  • سال: 

    2006
  • دوره: 

    -
  • شماره: 

    -
  • صفحات: 

    207-217
تعامل: 
  • استنادات: 

    1
  • بازدید: 

    54
  • دانلود: 

    0
کلیدواژه: 
چکیده: 

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 54

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resourcesدانلود 0 مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resourcesاستناد 1 مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resourcesمرجع 0
اطلاعات دوره: 
  • سال: 

    2016
  • دوره: 

    7
  • شماره: 

    1 (23)
  • صفحات: 

    23-34
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    408
  • دانلود: 

    0
چکیده: 

Finding frequent patterns plays a key role in exploring Association patterns, correlation, and many other interesting relationships that are applicable in TDB. Several Association Rule mining algorithms such as Apriori, FP-Growth, and Eclat have been proposed in the literature. FP-Growth algorithm construct a tree structure from transaction database and recursively traverse this tree to extract frequent patterns which satisfies the minimum support in a depth first search manner. Because of its high efficiency, several frequent pattern mining methods and algorithms have used FP-Growth’s depth first exploration idea to mine frequent patterns. These algorithms change the FP-tree structure to improve efficiency. In this paper, we propose a new frequent pattern mining algorithm based on FP-Growth idea which is using a bit matrix and a linked list structure to extract frequent patterns. The bit matrix transforms the dataset and prepares it to construct as a linked list which is used by our new FPBitLink Algorithm. Our performance study and experimental results show that this algorithm outperformed the former algorithms.

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 408

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نویسندگان: 

PATIL B. | DURGA T.

اطلاعات دوره: 
  • سال: 

    2010
  • دوره: 

    -
  • شماره: 

    2
  • صفحات: 

    330-334
تعامل: 
  • استنادات: 

    1
  • بازدید: 

    127
  • دانلود: 

    0
کلیدواژه: 
چکیده: 

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 127

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مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
اطلاعات دوره: 
  • سال: 

    1394
  • دوره: 

    3
  • شماره: 

    2
  • صفحات: 

    131-140
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    806
  • دانلود: 

    0
چکیده: 

متن کامل این مقاله به زبان انگلیسی می باشد، لطفا برای مشاهده متن کامل مقاله به بخش انگلیسی مراجعه فرمایید.لطفا برای مشاهده متن کامل این مقاله اینجا را کلیک کنید.

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 806

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نویسندگان: 

LUCAS R. | ROWLANDS A.

اطلاعات دوره: 
  • سال: 

    2007
  • دوره: 

    62
  • شماره: 

    3
  • صفحات: 

    165-185
تعامل: 
  • استنادات: 

    1
  • بازدید: 

    134
  • دانلود: 

    0
کلیدواژه: 
چکیده: 

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 134

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نویسندگان: 

MOBASHER B. | DAI H. | LUO T.

اطلاعات دوره: 
  • سال: 

    2001
  • دوره: 

    3
  • شماره: 

    -
  • صفحات: 

    9-15
تعامل: 
  • استنادات: 

    1
  • بازدید: 

    203
  • دانلود: 

    0
کلیدواژه: 
چکیده: 

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

بازدید 203

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اطلاعات دوره: 
  • سال: 

    1402
  • دوره: 

    13
  • شماره: 

    3
  • صفحات: 

    105-121
تعامل: 
  • استنادات: 

    0
  • بازدید: 

    171
  • دانلود: 

    14
چکیده: 

A B S T R A C T Temperature is one of the climate elements that has fluctuated a lot over time. When these fluctuations increase and decrease more than normal and are placed in the upper and lower regions of the statistical distribution, if continued, it can lead to the creation of heating and cooling waves. The purpose of this study is to analyze the Temporal and spatial changes in heating and cooling waves in Iran during a period of 50 years. For this purpose, the temperature of 663 synoptic stations from 1962 to 2004 was obtained from the Esfazari database. Then, in order to complete this database, the daily temperature from 2004 to 2011 was obtained from the Meteorological Organization of the country and added to the aforementioned database. In order to perform calculations and draw maps, Matlab, grads and Surfer software have been used. The results of this study showed that the index of cooling waves and heating waves, while having a direct effect on each other, had an increasing trend in most of the area of Iran. The statistical distribution of the index of cooling waves is more heterogeneous than that of the index of heating waves. So that the spatial variation coefficient for cold waves is 84.22%. Also, the index of cooling waves has more spatial variability. The highest common diffraction of the index of heating and cooling waves has been seen in the northwest, east and along the Zagros mountains. Analysis of the indexes trends show that heat waves have intensified in 65.8% of Iran and the intensity of cold waves has decreased in 48.5% of Iran Extended Abstract Introduction Temperature is one of the major climatic variables, which it has a direct impact on different aspects of human life. It plays an essential role in the growth of crops and is considered a key driver of the biological system(Reicosky et al, 1988). It is associated with several types of extremes, for example, heat and cold waves which caused human societies maximum damage. Past occurrences of heat waves hitherto had significant impacts on several aspects of society. Have increased Mortality and morbidity. Ecosystems can be affected, as well as increased pressure on infrastructures that support society, such as water, transportation, and energy(Dewce, 2016). The long-term change of extreme temperatures has a key role in climatic change. The form of statistical distribution and the variability of mean values and also extreme event indicate a change in the region. It can be a small relative change in the mean as a result of a large change in the probability of extreme occurrence. Also, the variation in temperature data variance is significantly more important than the mean, for assessing the extreme occurrence of climate(Toreti and Desiato, 2008). The average surface temperature has increased the world between 0.56 and 0.92 ° C over the past 100 years(IPCC, 2007). Meanwhile, it was in the Middle East, the average daily temperature increased by 0.4-0.5 ° C in decades(Kostopoulou et al, 2014; Tanarhte et al, 2012). Considering that not many studies have been done in the field of spatio-Temporal Variations of the heating and cooling waves thresholds in Iran, in this study, the spatio-Temporal Variations of the heating and cooling waves thresholds in Iran during 50 years were examined and analyzed.   Methodology The daily temperature from the beginning of the year 21/03/1967 to 19/05/2005 was obtained from the Esfazari database prepared by Dr. Masoudian at the University of Isfahan. In order to increase the time resolution of the mentioned database, the daily temperature of observations from 05/21/2005 to 05/12/2012 has been added to the mentioned database using the same method, and the exact spatial resolution (15 x 15 km) is used as a database. Threshold indices of heating waves are the average numbers between the 95th and 99th percentiles, that is, the extreme hot threshold to the limit of excessively extreme hot. For extreme cool, from the 5th percentile down to zero is used. Of course, a condition was added to these thresholds, which is that these thresholds must be repeated two days in a row. These thresholds were extracted for each day in the 50 years of the study period and used as the original database. In order to analyze the relationship between cooling and heating waves, Pearson's correlation coefficient was used and regression was used to analyze the trend.   Results and discussion The average of cold waves was 5.26 ° C and for the heat waves is 30.20° C. Generally, if the temperature is upper or lower than this threshold, it is considered as hot or cold temperatures. A comparison of the median, mode, and average of cold waves with heat waves shows that the distribution is more heterogeneous for cold waves and its CV is 84.22%. In southern Iran, the average threshold heat waves are higher. This situation can be caused by the effects of subtropical high-pressure radiation, low latitude, and proximity to the sea. Though the threshold is higher in these areas, fewer fluctuations and changes are seen in the area. Heights moderate the temperature so they pose a minimum threshold for heat waves i.e. an iso-threshold of 25 ° C is consistent along the Zagros mountain chains, but in the west and east of Zagros Mountains, the threshold of heat waves is increased. Heat waves have increased in most areas of the country. So nearly 85 percent of the Iran has been an increasing trend, of which 65.8 percent is statistically significant at the 95% confidence level. Still, more areas of the country (60 percent) have a trend between 0.00828 and 0.00161. As can be seen, only 15% of the land area (including the southwest and northwest of the Country) had decreased heat waves. Cold waves, in most parts of the country, have a Positive Trend. However, about 25 percent of the study area's cold waves have a negative trend. they are located in areas higher than Latitude 30°. The largest decline of the wave's trend along the country is highlands. Nowadays, most of the country, has a trend between 0.01494 and 0.00828 ° C, respectively. Conclusion Common changes and effects of heat and cold waves had a direct relationship in many parts of the country. It is remarkable common variance in the East reached 55 percent, according to statistical significance. In some areas of the northwest and southwest, which have been impressive heights, the common variance is 40 percent. This common variance in mountains area has been high values. Investigation of heat waves trend shows that 65.8% of Iran significant positive trend and 7.1% significant negative trend. Also, the cold waves trend has indicated a 48.5% significant positive trend and a 10.8% significant negative trend. Climate change and global warming have changed the frequency and severity of temperature extremes. The present study, by examining the number of warm waves, concluded that the warm waves have increased in magnitude in 65.8% of the Iran zone. Also, the study of the cold waves trend showed that 48.5 percent of Iran had a positive trend, which means that the amount of temperature in the cold waves increased In other words, the severity of the cold has been reduced And only 10.8 percent of Iran had a negative cold wave trend And it shows the intensity of these waves is reduced.   Funding There is no funding support.   Authors’ Contribution The authors contributed equally to the conceptualization and writing of the article. All of the authors approthe contenttent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest The authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

شاخص‌های تعامل:   مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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