STWalk: Learning Trajectory Representations in Temporal Graphs

Analyzing the temporal behavior of nodes in time-varying graphs is useful for many applications such as targeted advertising, community evolution and outlier detection. In this paper, we present a novel approach, STWalk, for learning trajectory representations of nodes in temporal graphs. The proposed framework makes use of structural properties of graphs at current and previous time-steps to learn effective node trajectory representations. STWalk performs random walks on a graph at a given time step (called space-walk) as well as on graphs from past time-steps (called time-walk) to capture the spatio-temporal behavior of nodes. We propose two variants of STWalk to learn trajectory representations. In one algorithm, we perform space-walk and time-walk as part of a single step. In the other variant, we perform space-walk and time-walk separately and combine the learned representations to get the final trajectory embedding. Extensive experiments on three real-world temporal graph datasets validate the effectiveness of the learned representations when compared to three baseline methods. We also show the goodness of the learned trajectory embeddings for change point detection, as well as demonstrate that arithmetic operations on these trajectory representations yield interesting and interpretable results.Comment: 10 pages, 5 figures, 2 table

Character of National University- A Conceptual Framework

The paper situates India’s global position with respect to its R&D and patent development and then highlights the current status of university system in India as a causative factor since majority of universities are busy in teaching merely how to qualify a paper-pencil test without much impetus on Research and Development. The paper also presents the perceived scenario of a national university and its characteristics. It also suggests ways in which universities can prioritize to produce researchers and innovators

Labeling topics with images using a neural network

Topics generated by topic models are usually represented by lists of t terms or alternatively using short phrases or images. The current state-of-the-art work on labeling topics using images selects images by re-ranking a small set of candidates for a given topic. In this paper, we present a more generic method that can estimate the degree of association between any arbitrary pair of an unseen topic and image using a deep neural network. Our method achieves better runtime performance O(n) compared to O(n2) for the current state-of-the-art method, and is also significantly more accurate

Effect of mindfulness on online impulse buying: Moderated mediation model of problematic internet use and emotional intelligence

Introduction: Online impulse buying behavior is an unplanned urge to buy a product or service in an online setting and it has several negative consequences for customers, such as guilt and financial distress, and e-commerce firms, such as higher returns and customer complaints. Evidently, it is important to examine the various psychological processes which may assist in a better understanding, therefore addressing the high prevalence of online impulse buying. This study builds upon self-regulation theory to explore how mindfulness influences online impulse buying, and examines problematic internet use as a mediator in the relationship between mindfulness and online impulse buying. Further, this study investigates how emotional intelligence as a moderator plays the role of a suppressant on the adverse impact of problematic Internet use which fuels online impulse buying. Method: A total of 598 individuals working with various servicebased industries responded to the questionnaire. Multiple regression and moderated mediation analysis was used using SPSS and AMOS for analyzing the data. Result: Problematic internet use mediates the relationship between mindfulness and online impulse buying behavior. Emotional intelligence negatively moderates the relationship between problematic internet use and online impulse buying behavior. Discussion: This study findings outlined the inverse relationship of mindfulness & online impulse buying, along with the mediating effect of problematic internet use between mindfulness and online impulse buying. Further, this study showed how emotional intelligence played an important role as a moderator by suppressing the adverse impact of problematic Internet use and preventing online impulse buying. The study offers implications to online marketers in regulating the unplanned purchase process—while minimizing uninhibited buying behavior that leads to regret, and the subsequent intention to return products. Further, social and theoretical implications are discussed

MARKET ANALYSIS AND POTENTIAL OF UAV SYSTEMS FOR MONITORING &CARTOGRAPHY IN ECOLOGY, AGRICULTURE & FORESTRY

This paper describes recent research into Aerial Photography, Cartography and Monitoring Capa-bilities and Technologies of UAV products currently available into the market. It reviews advancement of small electric powered unmanned air vehicle (UAV) capabilities. Specifically, topics under consideration were Aerial photography and its two uses, Cartography and Monitoring within the context of proposed exploitation of UAV for Planning, control and management in Agriculture, Forestry and Ecology. In the end a design and development of a new micro-UAV “Sparrow-S” is projected

Chess is hard even for a single player

We introduce a generalization of "Solo Chess", a single-player variant of the game that can be played on chess.com. The standard version of the game is played on a regular 8 x 8 chessboard by a single player, with only white pieces, using the following rules: every move must capture a piece, no piece may capture more than 2 times, and if there is a King on the board, it must be the final piece. The goal is to clear the board, i.e, make a sequence of captures after which only one piece is left. We generalize this game to unbounded boards with $n$ pieces, each of which have a given number of captures that they are permitted to make. We show that Generalized Solo Chess is NP-complete, even when it is played by only rooks that have at most two captures remaining. It also turns out to be NP-complete even when every piece is a queen with exactly two captures remaining in the initial configuration. In contrast, we show that solvable instances of Generalized Solo Chess can be completely characterized when the game is: a) played by rooks on a one-dimensional board, and b) played by pawns with two captures left on a 2D board. Inspired by Generalized Solo Chess, we also introduce the Graph Capture Game, which involves clearing a graph of tokens via captures along edges. This game subsumes Generalized Solo Chess played by knights. We show that the Graph Capture Game is NP-complete for undirected graphs and DAGs.Comment: 22 pages, a slightly shorter version to appear in FUN 202