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Dive into the research topics where Lakisha L. Simmons is active.

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Featured researches published by Lakisha L. Simmons.


ieee international conference on cyber technology in automation control and intelligent systems | 2014

A qualitative analysis of an ontology based issue resolution system for cyber attack management

Chris B. Simmons; Sajjan G. Shiva; Lakisha L. Simmons

Cyber-attacks are increasing at an alarming rate and the attackers have progressively improved in devising attacks towards specific targets. To further develop the area of cyber-attack communication, we propose an ontology based issue resolution system used to identify and defend against cyber-attacks. The issue resolution system (IRS) facilitates attack discovery and suggestive defenses for a small to medium sized organizations. We validate our IRS Ontology using qualitative study of security expert professionals and highlight future work intended to simulate the IRS in a virtual attack test environment.


Journal of Computer Information Systems | 2015

Terrorism Information Extraction from Online Reports

Sumali Conlon; Alan S. Abrahams; Lakisha L. Simmons

Many documents containing information about intelligence and security issues are available both in printed and electronic formats. In this research, we built an experimental system to extract intelligence and security information from electronic documents. Our system, CAINES, is based on a knowledge engineering approach and relies on sublanguage analysis techniques. CAINES performs syntactic and semantic analysis and uses lexicons of various categories of terms. The system is able to extract certain types of information from reports on terrorist incidents posted by the National Counterterrorism Center (NCTC), such as what happened and the results of the incidents.


International Journal of Business and Systems Research | 2010

The impact of small business B2B virtual community commitment on brand loyalty

Lakisha L. Simmons; Russell W. Clayton

In effort to focus research attention on emerging business-to-business (B2B) virtual communities (VCs), we review and extend business-to-consumer (B2C) literature, resource-advantage theory and relationship marketing to describe how community-hosting organisations build brand loyalty in B2B markets. We explain how functional usefulness, system quality, business opportunity, dialogue initiation and response frequency impact B2B VC commitment and brand loyalty towards the community-hosting organisation. Results of this study support hypotheses that B2B VCs critically impact relationship marketing. Further, functional usefulness, system quality, business opportunity, dialogue initiation and response frequency impact B2B community commitment and brand loyalty.


ACM Sigmis Database | 2013

Extraction of financial information from online business reports

Lakisha L. Simmons; Sumali Conlon

CAINES, Content Analysis and INformation Extraction System, employs a semantic based information extraction (IE) methodology through a design science approach to extract unstructured text from the Web. Our system was knowledge-engineered and tested on an active business database by experts who use the database regularly to perform their job functions. We believe that by heavily involving business experts, we are able to advance our thinking about IS research. CAINES extracts information to meet three objectives that were deemed important by our experts: (1) understand what current market conditions impacted the growth of certain balance sheets (2) summarize managements discussion of potential risks and uncertainties (3) identify significant financial activities including mergers, acquisitions, and new business segments. These objectives were developed based on the advice of financial experts who regularly analyze financial reports. A total of 21 online business reports from the EDGAR database, each averaging about 100 pages long, were used in this study. Based on financial expert opinions, extraction rules were created to extract information from financial reports. Using CAINES, one can extract information about global and domestic market conditions, market condition impacts, and information about the business outlook. User testing of CAINES resulted in recall of 85.91%, precision of 87.16%, and an F-measure of 86.46%. Speed with CAINES was also greater than manually extracting information. Users agreed that CAINES quickly and easily extracts unstructured information from financial reports on the EDGAR database. This study highlights the significance of creating a semantic based IE system that addresses practical business issues and solves a true business problem with the knowledge of business experts.


Journal of Computer Information Systems | 2015

A Computer Aided Content Analysis of Online Reviews

Lakisha L. Simmons; Surma Mukhopadhyay; Sumali Conlon; Jun Yang


Archive | 2010

Automatic Translation in Multilingual Electronic Meetings

Milam Aiken; Mina Park; Lakisha L. Simmons; Tobin Lindblom


Journal of Computing Sciences in Colleges | 2010

Gaps in the computer science curriculum: an exploratory study of industry professionals

Chris B. Simmons; Lakisha L. Simmons


Journal of STEM Education: Innovations and Research | 2011

TeleEducation Initiatives for Sub-Saharan Africa: The Case of the African Virtual University in Kenya

Derkirra Wilkerson; Lakisha L. Simmons; Victor Mbarika; Carlos A. Thomas; Irene Mbarika; Clive Tsuma; Tamiara L. Wade


Decision Sciences Journal of Innovative Education | 2012

A Cultural Comparison of Trust in eLearning Artifacts

Lakisha L. Simmons; Chris B. Simmons; Mario Hayek; Rachida Parks; Victor Mbarika


Archive | 2011

A FRAMEWORK AND DEMO FOR PREVENTING ANTI-COMPUTER FORENSICS

Chris B. Simmons; Danielle L. Jones; Lakisha L. Simmons

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Sumali Conlon

University of Mississippi

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Milam Aiken

University of Mississippi

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Victor Mbarika

Southern University and A

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Carlos A. Thomas

Louisiana State University

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Mina Park

Northern State University

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