Konstantin Bauman

Temple University | TU · Fox School of Business and Management

Context has been an important topic in recommender systems over the past two decades. A standard representational approach to context assumes that contextual variables and their structures are known in an application. Most of the prior CARS papers following representational approach manually selected and considered only a few crucial contextual var...

In this paper, we study an important problem of parsing contextual information from user reviews for recommendation purposes. First, we study the ways contextual information is expressed in user reviews and obtain novel insights about it. Among other things, we demonstrate that such type of information tends to appear at the beginning of the review...

Contextual information has been widely recognized as an important modeling dimension both in social sciences and in computing. In particular, the role of context has been recognized in enhancing recommendation results and retrieval performance. While a substantial amount of existing research has focused context-aware recommender systems (CARS), man...

In a standard cluster analysis, such as k-means, in addition to clusters locations and distances between them it is important to know if they are connected or well separated from each other. The main focus of this paper is discovering the relations between the resulting clusters. We propose a new method which is based on pairwise overlapping k-mean...

We study the problem of providing recommendations to students that help them in their studies. To address this problem, we present an approach of providing recommendations of remedial learning materials to students that fill the gaps in their knowledge of the subject in the courses they take. According to this method, we first identify gaps in the...

In this paper, we propose a recommendation technique that not only can recommend items of interest to the user as traditional recommendation systems do but also specific aspects of consumption of the items to further enhance the user experience with those items. For example, it can recommend the user to go to a specific restaurant (item) and also o...

This article presents a novel approach to detecting emergency events, such as power outages, that utilizes social media users as “social sensors” for virtual detection of such events. The proposed new method is based on the analysis of the Twitter data that leads to the detection of Twitter discussions about these emergency events. The method descr...

In a standard cluster analysis, such as k-means, in addition to clusters locations and distances between them, it's important to know if they are connected or well separated from each other. The main focus of this paper is discovering the relations between the resulting clusters. We propose a new method which is based on pairwise overlapping k-mean...

In this paper, we presented a novel semi-supervised one-class classification algorithm which assumes that class is linearly separable from other elements. We proved theoretically that class is linearly separable if and only if it is maximal by probability within the sets with the same mean. Furthermore, we presented an algorithm for identifying suc...

We prove that the square-to-linear ratio of a regular Peano curve that maps the unit interval onto the unit square is at least five.

The paper presents a new method of discovering relevant contextual information from the user-generated reviews in order to provide better recommendations to the users when such reviews complement traditional ratings used in recommender systems. In particular, we classify all the user reviews into the "context rich" specific and "context poor" gener...

The problem of the estimation of the click through rate on advertisements that are placed on a search-engine results page is discussed. The proposed methods improved the prediction quality (both in terms of likelihood metrics and the principle parameters of the engine). The cases of advertisement displays are considered when the history of an ad is...

The problem of the estimation of the click-through rate on advertisements that are placed on a search􏴣engine results page is discussed. The proposed methods improved the prediction quality (both in terms of likelihood metrics and the principle parameters of the engine). The cases of advertisement displays are considered when the history of an ad is...

This paper completes the analysis (begun by E.V. Shchepin and the author in 2008) of regular Peano curves of genus 9 in search of a curve with the minimum square-to-linear ratio. One-side regular Peano curves of genus 9 are considered, and, among these curves, a class of minimal curves with a square-to-linear ratio of 5 2 3 is singled out. A new la...

A Peano curve p(x) with maximum square-to-linear ratio |p(x)−p(y)|2/|x−y| equal to 5 2/3 is constructed; this ratio is smaller than that of the classical Peano-Hilbert curve, whose maximum square-to-linear ratio is 6. The curve constructed is of fractal genus 9 (i.e., it is decomposed into nine fragments that are similar to the whole curve) and of...

It is proved that the maximum value of the ratio |p(x) − p(y)|2/|x − y| for the Peano-Hilbert curve p: [0, 1] = I → I 2 is equal to 6.