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Department of Information Systems & Computer Science Faculty Publications

2017

Articles 1 - 6 of 6

Full-Text Articles in Physical Sciences and Mathematics

Time-Series Link Prediction Using Support Vector Machines, Proceso L. Fernandez Jr, Jan Miles Co Jun 2017

Time-Series Link Prediction Using Support Vector Machines, Proceso L. Fernandez Jr, Jan Miles Co

Department of Information Systems & Computer Science Faculty Publications

The prominence of social networks motivates developments in network analysis, such as link prediction, which deals with predicting the existence or emergence of links on a given network. The Vector Auto Regression (VAR) technique has been shown to be one of the best for time-series based link prediction. One VAR technique implementation uses an unweighted adjacency matrix and five additional matrices based on the similarity metrics of Common Neighbor, Adamic-Adar, Jaccard’s Coefficient, Preferential Attachment and Research Allocation Index. In our previous work, we proposed the use of the Support Vector Machines (SVM) for such prediction task, and, using the same …

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Infodemiology For Syndromic Surveillance Of Dengue And Typhoid Fever In The Philippines, Ma. Regina Justina E. Estuar, Kennedy E. Espina Jan 2017

Infodemiology For Syndromic Surveillance Of Dengue And Typhoid Fever In The Philippines, Ma. Regina Justina E. Estuar, Kennedy E. Espina

Department of Information Systems & Computer Science Faculty Publications

Finding determinants of disease outbreaks before its occurrence is necessary in reducing its impact in populations. The supposed advantage of obtaining information brought by automated systems fall short because of the inability to access real-time data as well as interoperate fragmented systems, leading to longer transfer and processing of data. As such, this study presents the use of realtime latent data from social media, particularly from Twitter, to complement existing disease surveillance efforts. By being able to classify infodemiological (health-related) tweets, this study is able to produce a range of possible disease incidences of Dengue and Typhoid Fever within the …

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A Multi-Model Approach In Developing An Intelligent Assistant For Diagnosis Recommendation In Clinical Health Systems, Christian E. Pulmano, Ma. Regina Justina E. Estuar Jan 2017

A Multi-Model Approach In Developing An Intelligent Assistant For Diagnosis Recommendation In Clinical Health Systems, Christian E. Pulmano, Ma. Regina Justina E. Estuar

Department of Information Systems & Computer Science Faculty Publications

Clinical health information systems capture massive amounts of unstructured data from various health and medical facilities. This study utilizes unstructured patient clinical text data to develop an intelligent assistant that can identify possible related diagnoses based on a given text input. The approach applies a one-vs-rest binary classification technique wherein given an input text data, it is identified whether it can be positively or negatively classified for a given diagnosis. Multi-layer Feed-Forward Neural Network models were developed for each individual diagnosis case. The task of the intelligent assistant is to iterate over all the different models and return those that …

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Discovering Conversation Spaces In The Public Discourse Of Gender Violence: A Comparative Between Two Different Contexts, Meliza M. De La Paz, Ma. Regina Justina E. Estuar, John Noel C. Victorino Jan 2017

Discovering Conversation Spaces In The Public Discourse Of Gender Violence: A Comparative Between Two Different Contexts, Meliza M. De La Paz, Ma. Regina Justina E. Estuar, John Noel C. Victorino

Department of Information Systems & Computer Science Faculty Publications

A huge factor in gender-based violence is perception and stigma, revealed by public discourse. Topic modelling is useful for discourse analysis and reveals prevalent topics and actors. This study aims to find and compare examples of collectivist and individualist conversation spaces of gendered violence by applying Principal Component Analysis, NGram analysis and word association in two gender violence cases which occured in the different contexts of the Philippines and the United States. The data from the Philippines consist of 2010-2011 articles on the 1991 Vizconde Massacre and the data from the United States consist of 2016-2017 articles from the 2015 …

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Exploratory Analysis Of Discourses Between Students Engaged In A Debugging Task, Ma. Mercedes T. Rodrigo Jan 2017

Exploratory Analysis Of Discourses Between Students Engaged In A Debugging Task, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

This paper determined if and how high-performing and low-performing students differed in the language that they used as they collaborated on a debugging task. 180 students worked in pairs to debug 12 small programs with known errors. Students were segregated into high and low achievement levels based on the number of bugs they found. Chat transcripts from the pairs were analyzed using the Linguistic Inquiry and Word Count (LIWC) software. We found that high- and low-performing students only varied in terms of their use of words that implied discrepancy and sadness.

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Designing An Intervention For Novice Programmers Based On Meaningful Gamification: An Expert Evaluation, Jenilyn L. Agapito, Ma. Mercedes T. Rodrigo Jan 2017

Designing An Intervention For Novice Programmers Based On Meaningful Gamification: An Expert Evaluation, Jenilyn L. Agapito, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

Gamification is defined as the addition of game-like elements and mechanics to non-game contexts to encourage certain desired behaviors. It is becoming a popular classroom intervention used in computer science instruction, including CS1, the first course computer science students take. It is being operationalized to enhance students' learning experience and achievement. However, existing studies have mostly implemented reward-based game elements which have resulted to contrasting behaviors among the students. Meaningful gamification, characterized as the use of game design elements to encourage users build internal motivation to behave in a certain way, is contended to be a more effective approach. The …

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