The COVID pandemic has allowed people to reflect and explore their emotions,their strengths and deficiencies,how they affect them and how to address them.The globally observed,pandemic-induced social distancing,has al...The COVID pandemic has allowed people to reflect and explore their emotions,their strengths and deficiencies,how they affect them and how to address them.The globally observed,pandemic-induced social distancing,has also precipitated disturbances in the domain of mental health.Almost the entire population worldwide,went through a series of lockdowns,resulting in people getting isolated,some feeling trapped in the stressful environment of a forced shared living places-homes.This precipitated in exposing conflicts of various types and degrees,encountering a common emotion-grief.With no access to professionals in traditional format,the online networking boom has given a ray of hope to the people in need.This research-based article explores how online therapy is being seen as a reliable and important tool for people needing help with mental health issues,by conducting a survey on the youth of Delhi-NCR.This research article explores the ways in which people reached mental health professionals and how internet-based therapies increased manifolds during pandemic.A total of 54%participants of the survey agreed to engage in online therapy practice in situation of need.展开更多
针对互联网舆情挖掘领域的特点，提出了一种基于向量空间模型VSM的文本聚类算法STCC（Similarity Threshold Control Clustering BasedVSM）。该算法按照层次聚类从下至上凝聚的策略，获取初始簇信息，然后根据K-means算法的思想以设置...针对互联网舆情挖掘领域的特点，提出了一种基于向量空间模型VSM的文本聚类算法STCC（Similarity Threshold Control Clustering BasedVSM）。该算法按照层次聚类从下至上凝聚的策略，获取初始簇信息，然后根据K-means算法的思想以设置的聚类相似度阈值作为度量来合并簇。该算法结合层次聚类和K-means算法的优点，克服其缺点。与层次聚类相比，每一次聚类时不需要比较所有簇之间的相似度，降低了时间复杂度，提高了聚类的效率；与K—means算法相比，不需要确定K值，灵活性更高。通过实验表明，该算法聚类效果好，实用性高，适合大规模的文本聚类。展开更多
文摘The COVID pandemic has allowed people to reflect and explore their emotions,their strengths and deficiencies,how they affect them and how to address them.The globally observed,pandemic-induced social distancing,has also precipitated disturbances in the domain of mental health.Almost the entire population worldwide,went through a series of lockdowns,resulting in people getting isolated,some feeling trapped in the stressful environment of a forced shared living places-homes.This precipitated in exposing conflicts of various types and degrees,encountering a common emotion-grief.With no access to professionals in traditional format,the online networking boom has given a ray of hope to the people in need.This research-based article explores how online therapy is being seen as a reliable and important tool for people needing help with mental health issues,by conducting a survey on the youth of Delhi-NCR.This research article explores the ways in which people reached mental health professionals and how internet-based therapies increased manifolds during pandemic.A total of 54%participants of the survey agreed to engage in online therapy practice in situation of need.
文摘针对互联网舆情挖掘领域的特点，提出了一种基于向量空间模型VSM的文本聚类算法STCC（Similarity Threshold Control Clustering BasedVSM）。该算法按照层次聚类从下至上凝聚的策略，获取初始簇信息，然后根据K-means算法的思想以设置的聚类相似度阈值作为度量来合并簇。该算法结合层次聚类和K-means算法的优点，克服其缺点。与层次聚类相比，每一次聚类时不需要比较所有簇之间的相似度，降低了时间复杂度，提高了聚类的效率；与K—means算法相比，不需要确定K值，灵活性更高。通过实验表明，该算法聚类效果好，实用性高，适合大规模的文本聚类。
