Canonical Trends: Detecting Trend Setters in Web Data
نویسندگان
چکیده
Much information available on the web is copied, reused or rephrased. The phenomenon that multiple web sources pick up certain information is often called trend. A central problem in the context of web data mining is to detect those web sources that are first to publish information which will give rise to a trend. We present a simple and efficient method for finding trends dominating a pool of web sources and identifying those web sources that publish the information relevant to a trend before others. We validate our approach on real data collected from influential technology news feeds.
منابع مشابه
On the Detection of Trends in Time Series of Functional Data
A sequence of functions (curves) collected over time is called a functional time series. Functional time series analysis is one of the popular research areas in which statistics from such data are frequently observed. The main purpose of the functional time series is to predict and describe random mechanisms that resulted in generating the data. To do so, it is needed to decompose functional ti...
متن کاملDesigning a System for Trend Analysis of Users in Website Surfing in Iran Using Data Mining and Text Mining Algorithms
Background and Aim: As of the entrance of web surfing to the lifestyle of a vast majority of people in the society and the need for a more accurate social and cultural policy making in the field, authors intended to analyze the behavior of the society users in viewing different websites so as to help politicians and practitioners. Methods: Design science research method is used in this research...
متن کاملAnalysis of climate data using statistical methods on west of the Caspian Sea
Abstract Long-term observational data are essential for detecting and understanding local, regional and global climate change. The goal of this paper is to consider climate data of west of the Caspian Sea for any trends in Annual means of 2m temperature and precipitation at the stations of Anzali, Rasht, Astara and Lahijan for 1956-2018 period. Some inconsistencies in the data were found. Our ...
متن کاملTrend Mining with Semantic-Based Learning
Mining trends by analyzing text streams could enhance the standard trend analysis based on numeric data. The use of qualitative information in the process of trend recognition, in addition to that of quantitative data, requires new analysis techniques. Since Semantic Web enables the appropriate and advantageous formalization of knowledge, we propose to include formalized expert knowledge in the...
متن کاملتحلیل روند عوامل اقلیمی در شهرهای بزرگ ایران
Climate change has important effects on earth environment and human life. Therefor, investigation and study of climate change is very essential. This study investigated rainfall, temperature, relative humidity and wind variability by analyzing data for annual and monthly climatic factors collected at 13 synoptic stations (industrial cities of Iran) by using Mann-Kendall test. The results of mon...
متن کامل