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Personalized Search Using User Preferences on Social Media
Electronics ( IF 2.6 ) Pub Date : 2022-09-24 , DOI: 10.3390/electronics11193049
Kyoungsoo Bok , Jinwoo Song , Jongtae Lim , Jaesoo Yoo

In contrast to traditional web search, personalized search provides search results that take into account the user’s preferences. However, the existing personalized search methods have limitations in providing appropriate search results for the individual’s preferences, because they do not consider the user’s recent preferences or the preferences of other users. In this paper, we propose a new search method considering the user’s recent preferences and similar users’ preferences on social media analysis. Since the user expresses personal opinions on social media, it is possible to grasp the user preferences when analyzing the records of social media activities. The proposed method collects user social activity records and determines keywords of interest using TF-IDF. Since user preferences change continuously over time, we assign time weights to keywords of interest, giving many high values to state-of-the-art user preferences. We identify users with similar preferences to extend the search results to be provided to users because considering only user preferences in personalized searches can provide narrow search results. The proposed method provides personalized search results considering social characteristics by applying a ranking algorithm that considers similar user preferences as well as user preferences. It is shown through various performance evaluations that the proposed personalized search method outperforms the existing methods.

中文翻译:

在社交媒体上使用用户偏好进行个性化搜索

与传统的网络搜索相比,个性化搜索提供了考虑到用户偏好的搜索结果。然而,现有的个性化搜索方法在提供适合个人偏好的搜索结果方面存在局限性,因为它们没有考虑用户最近的偏好或其他用户的偏好。在本文中,我们提出了一种新的搜索方法,考虑了用户最近的偏好和相似用户对社交媒体分析的偏好。由于用户在社交媒体上表达个人意见,因此在分析社交媒体活动记录时可以掌握用户的喜好。所提出的方法收集用户社交活动记录并使用 TF-IDF 确定感兴趣的关键字。由于用户偏好会随着时间不断变化,我们为感兴趣的关键字分配时间权重,为最先进的用户偏好赋予许多高价值。我们识别具有相似偏好的用户以扩展要提供给用户的搜索结果,因为在个性化搜索中仅考虑用户偏好可以提供狭窄的搜索结果。所提出的方法通过应用考虑相似用户偏好以及用户偏好的排名算法来提供考虑社会特征的个性化搜索结果。通过各种性能评估表明,所提出的个性化搜索方法优于现有方法。我们识别具有相似偏好的用户以扩展要提供给用户的搜索结果,因为在个性化搜索中仅考虑用户偏好可以提供狭窄的搜索结果。所提出的方法通过应用考虑相似用户偏好以及用户偏好的排名算法来提供考虑社会特征的个性化搜索结果。通过各种性能评估表明,所提出的个性化搜索方法优于现有方法。我们识别具有相似偏好的用户以扩展要提供给用户的搜索结果,因为在个性化搜索中仅考虑用户偏好可以提供狭窄的搜索结果。所提出的方法通过应用考虑相似用户偏好以及用户偏好的排名算法来提供考虑社会特征的个性化搜索结果。通过各种性能评估表明,所提出的个性化搜索方法优于现有方法。
更新日期:2022-09-24
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