Infrastructure and Algorithms for Information Retrieval Based On Social Network Analysis/Mining

We will touch on such issues as the logical necessity of the laws of nature; objectivity, invariance and symmetry; theoretical physics and possible universes; entropy in

Abstract—Social Information Retrieval (SIR) exploits the user’s social data in order to refine the retrieval, for instance in the case where users with different backgrounds may

For example, in the queries (taken from the topics of Social Book Search 2016) “Help! I Need more books”, “New releases from authors that literally make you swoon...” or

Combining the user’s profile (term frequencies) with a query (binary) and then computing the matching score with textual documents containing thousands of terms raises different

The main idea of SQEL is to learn the feature representation (i.e., embedding vector) of the query, and use the learned feature vector to find the users with highest vector

In this paper we propose a novel method to learn the query embeddings [2, 14] using a simple and scalable technique and use it to measure similarity between user context queries

Searching information on the Web of Data requires user friendly approaches, similar to the ease of keyword-based search engines, but relying on the RDF. In this

I will describe the personality typology systems currently in use (MBTI, Big Five, Enneagram), the features and methods proposed for assigning personality, and the current state of