Business enterprises are facing many problems due to the increasing complexity and latency of the decision-making process due to the highly competitive and dynamic market scenarios. In addition, the amount of data to be analyzed has increased substantially. This has resulted in AI stepping in to assist decision makers to make better business decisions, reduce latency and enhance revenue opportunities.
Prophetia: Artificial Intelligence for TravelBox® Technology
B. B. A. Geethal
R. C. Gunasekara
M. H. M. Mafaz
C. D. T. Mathew
A. S. Perera
Machine learning for understanding the contextual semantics of tabular web sources
Identifying and extracting information from web tables is not a trivial task, and understanding the semantics of a web table proves to be even harder.
This paper introduces a machine learning based approach to understand the semantics in the data residing in tabular web sources. The approach includes suggesting features that reflect the characteristics of the content in the tables and analyze their impact on the accuracy of the classification process.
Machine Learning Approach to Recognize Subject Based Sentiment Values of Reviews
Moratuwa Engineering Research Conference (MERCon), 2016
Due to the increasing number of online interaction in travel industry, there is a rich corpus of textual information available online.To make sense of these information specially online reviews, the essential first step is to understand the semantics that lie therein. This paper discusses a system that uses machine learning based classifiers to label the entities found in text into semantic concepts defined in an ontology.
N. M. De Mel
H. H. Hettiarachchi
W. P. D. Madusanka
G. L. Malaka
A. S. Perera
Programmatic Implementation of the Karmarkar’s Algorithm for Vacation Package Synthesis Process Optimization
Packaging basic vacation components to generate the highest revenue is a hectic task for a tour operator. This would cost many man hours.
The paper presents a linear programming approach which ensures the maximum revenue to the tour operator, where all the contract constraints are satisfied. From LP model formulation to the solving algorithm and its results will be presented in this paper. Karmarkar’s Projective Scaling algorithm, which is the solving algorithm will be explained in the process, with its implementation approach
Agent-Based Framework for One-to-many Bilateral Negotiation in Online Trading
ACAN2016 The 9th International Workshop on Agent-based Complex Automated Negotiations Singapore
May 9, 2016
Existing Agent-Based Negotiation (ABN) frameworks for bargaining are based on the assumption that private information of agents such as reserve price and with fixed deadlines.
Real world bargaining scenarios, negotiators change their deadline due to their bargaining strategies, personal reasons or market issues. Existing Agent-Based Negotiation (ABN) frameworks are based on the assumption that private information of agents such as reserve price and with fixed deadlines which limits the usability and performance of the existing ABN approaches. This paper presents a global optimization model for offer generation in one-to-many bilateral negotiations that takes dynamism of the deadline into account. In this approach the agents profess a deadline that is shorter than the actual, thus pressurizing the opponent to get a quick counter offer and finally selects the best opponent to deal with.To support agents with incomplete information, the model incorporates Bayesian learning.
Implementation of 360-degree real time Video Stitching
This paper describes a solution for creating a 360-degree real time panoramic video stream from an array of webcams whose positions are fixed. The algorithm provides a mechanism to correct errors in positioning. Normalization of luminance is done to compensate for variance in lighting and picture quality of webcams.
V. G. Samarawickrama
DecisionAI: A framework to automate the decision making process
Information and Automation for Sustainability (ICIAfS)
2012 IEEE 6th International Conference
Accurate decision making is the key to make a business profitable. Decision support systems are used to make the decision making process accurate and easy. Even though there are many business specific decision support systems they cannot be used for general purpose decision making or outside their domain. DecisionAI provides a framework which can be used in any decision making domain with similar decision types and allows detailed analysis of data with the integrated intelligence.
K. T. Buddhika
D. P. Jayamanne
P. P. Wljegunawardana