User Profile Relationships using String Similarity Metrics in Social Networks
نویسنده
چکیده
This article reviews the problem of degree of closeness and interaction level in a social network by ranking users based on similarity score. This similarity is measured on the basis of social, geographic, educational, professional, shared interests, pages liked, mutual interested groups or communities and mutual friends. The technique addresses the problem of matching user profiles in its globality by providing a suitable matching framework able to consider all profiles’ attributes and finding the similarity by new ways of string metrics. It is able to discover the biggest possible number of profiles that are similar to the target user profile, which the existing techniques are unable to detect. Attributes were assigned weights manually; string and semantic similarity metrics were used to compare attributes values thus predicting the most similar profiles. Profile based similarity show the exact relationship between users and this similarity between user profiles reflects closeness and interaction between users.
منابع مشابه
Prediction of user's trustworthiness in web-based social networks via text mining
In Social networks, users need a proper estimation of trust in others to be able to initialize reliable relationships. Some trust evaluation mechanisms have been offered, which use direct ratings to calculate or propagate trust values. However, in some web-based social networks where users only have binary relationships, there is no direct rating available. Therefore, a new method is required t...
متن کاملProviding a Link Prediction Model based on Structural and Homophily Similarity in Social Networks
In recent years, with the growing number of online social networks, these networks have become one of the best markets for advertising and commerce, so studying these networks is very important. Most online social networks are growing and changing with new communications (new edges). Forecasting new edges in online social networks can give us a better understanding of the growth of these networ...
متن کاملSimilarity measurement for describe user images in social media
Online social networks like Instagram are places for communication. Also, these media produce rich metadata which are useful for further analysis in many fields including health and cognitive science. Many researchers are using these metadata like hashtags, images, etc. to detect patterns of user activities. However, there are several serious ambiguities like how much reliable are these informa...
متن کاملMerging Similarity and Trust Based Social Networks to Enhance the Accuracy of Trust-Aware Recommender Systems
In recent years, collaborative filtering (CF) methods are important and widely accepted techniques are available for recommender systems. One of these techniques is user based that produces useful recommendations based on the similarity by the ratings of likeminded users. However, these systems suffer from several inherent shortcomings such as data sparsity and cold start problems. With the dev...
متن کاملUsing Users' Activity Metrics for Link-Prediction in a Large Online Social Network
A considerable amount of recent research has been conducted on the link-prediction problem, that is the problem of accurately predicting edges that will be established between actors of a social network in a future time period [LNK07, LZ10]. In cooperation with the provider of a German social network site (SNS), we aim to contribute to this line of research by analyzing the link-formation and i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1408.3154 شماره
صفحات -
تاریخ انتشار 2014