Digital Commons Network^™

Invariant Spatial Information In Sketch Maps — A Study Of Survey Sketch Maps Of Urban Areas, Jia Wang, Angela Schwering

Journal of Spatial Information Science

It is commonly recognized that free-hand sketch maps are influenced by cognitive impacts and therefore sketch maps are incomplete, distorted, and schematized. This makes it difficult to achieve a one-to-one alignment between a sketch map and its corresponding geo-referenced metric map. Nevertheless, sketch maps are still useful to communicate spatial knowledge, indicating that sketch maps contain certain spatial information that is robust to cognitive impacts. In existing studies, sketch maps are used frequently to measure cognitive maps. However, little work has been done on invariant spatial information in sketch maps, which is the information of spatial configurations representing correctly the …

Development And Evaluation Of A Geographic Information Retrieval System Using Fine Grained Toponyms, Damien Palacio, Curdin Derungs, Ross S. Purves

Journal of Spatial Information Science

Geographic information retrieval (GIR) is concerned with returning information in response to an information need, typically expressed in terms of a thematic and spatial component linked by a spatial relationship. However, evaluation initiatives have often failed to show significant differences between simple text baselines and more complex spatially enabled GIR approaches. We explore the effectiveness of three systems (a text baseline, spatial query expansion, and a full GIR system utilizing both text and spatial indexes) at retrieving documents from a corpus describing mountaineering expeditions, centred around fine grained toponyms. To allow evaluation, we use user generated content (UGC) in the …

Geological Heritage And Framework List Of The Geosites In Turkey, Nizamettin Kazanci, Fuat Şaroğlu, Yaşar Suludere

Bulletin of the Mineral Research and Exploration

Geosites and the special type of geosite called geological heritage are tangible materials such as rocks, fossils, minerals, sedimentary sequences, or structures about which there are results and/or documents of significant events in the geological history. A Framework List deciphers the geological events of the past without mentioning the localities or results. Ideally, there is only one Framework List for every country. The Framework List for Turkey proposed by this study includes 85 titles (frame) in 10 categories. The Stratigraphic and Volcanic-Metamorphic-Sedimentary Petrology categories are the richest for the Frameworks; however they two already contain the majority of the geosites …

Estimates Of Probable Dementia Prevalence From Population-Based Surveys Compared With Dementia Prevalence Estimates Based On Meta-Analyses, Kaarin J. Anstey, Richard A. Burns, Carole Birrell, David G. Steel, Kim M. Kiely, Mary A. Luszcz

Dr Carole Birrell

Background: National data on dementia prevalence are not always available, yet it may be possible to obtain estimates from large surveys that include dementia screening instruments. In Australia, many of the dementia prevalence estimates are based on European data collected between 15 and 50 years ago. We derived populationbased estimates of probable dementia and possible cognitive impairment in Australian studies using the Mini-Mental State Examination (MMSE), and compared these to estimates of dementia prevalence from meta-analyses of European studies. Methods: Data sources included a pooled dataset of Australian longitudinal studies (DYNOPTA), and two Australian Bureau of Statistics National Surveys of …

Describing Images Using A Multilayer Framework Based On Qualitative Spatial Models, Tao Wang, Hui Shi

Baltic International Yearbook of Cognition, Logic and Communication

To date most research in image processing has been based on quantitative representations of image features using pixel values, however, humans often use abstract and semantic knowledge to describe and analyze images. To enhance cognitive adequacy and tractability, we here present a multilayer framework based on qualitative spatial models. The layout features of segmented images are defined by qualitative spatial models which we introduce, and represented as a set of qualitative spatial constraints. Assigned different semantic and context knowledge, the image segments and the qualitative spatial constraints are interpreted from different perspectives. Finally, the knowledge layer of the framework enables …

Social Learning Systems: The Design Of Evolutionary, Highly Scalable, Socially Curated Knowledge Systems, Nolan Hemmatazad

Student Work

In recent times, great strides have been made towards the advancement of automated reasoning and knowledge management applications, along with their associated methodologies. The introduction of the World Wide Web peaked academicians’ interest in harnessing the power of linked, online documents for the purpose of developing machine learning corpora, providing dynamical knowledge bases for question answering systems, fueling automated entity extraction applications, and performing graph analytic evaluations, such as uncovering the inherent structural semantics of linked pages. Even more recently, substantial attention in the wider computer science and information systems disciplines has been focused on the evolving study of social …

Intent Classification Of Short-Text On Social Media, Hemant Purohit, Guozhu Dong, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Social media platforms facilitate the emergence of citizen communities that discuss real-world events. Their content reflects a variety of intent ranging from social good (e.g., volunteering to help) to commercial interest (e.g., criticizing product features). Hence, mining intent from social data can aid in filtering social media to support organizations, such as an emergency management unit for resource planning. However, effective intent mining is inherently challenging due to ambiguity in interpretation, and sparsity of relevant behaviors in social data. In this paper, we address the problem of multiclass classification of intent with a use-case of social data generated during crisis …

A Machine-Aided Approach To Generating Grammar Rules From Japanese Source Text For Use In Hybrid And Rule-Based Machine Translation Systems, Sean Michael Jones

Theses and Dissertations

Many automatic machine translation systems available today use a hybrid of pure statistical translation and rule-based grammatical translations. This is largely due to the shortcomings of each individual approach, requiring a large amount of time for linguistics experts to hand-code grammar rules for a rule-based system and requiring large amounts of source text to generate accurate statistical models. By automating a portion of the rule generation process, the creation of grammar rules could be made to be faster, more efficient and less costly. By doing statistical analysis on a bilingual corpus, common grammar rules can be inferred and exported to …

Group Decision Making Using Comparative Linguistic Expression Based On Hesitant Intuitionistic Fuzzy Sets, Ismat Beg, Tabasam Rashid

Applications and Applied Mathematics: An International Journal (AAM)

We introduce a method for aggregation of experts’ opinions given in the form of comparative linguistic expression. An algorithmic form of technique for order preference is proposed for group decision making. A simple example is given by using this method for the selection of the best alternative as well as ranking the alternatives from the best to the worst.

Capstone Projects Mining System For Insights And Recommendations, Melvrivk Aik Chun Goh, Swapna Gottipati, Venky Shankararaman

Research Collection School Of Computing and Information Systems

In this paper, we present a classification based system to discover knowledge and trends in higher education students’ projects. Essentially, the educational capstone projects provide an opportunity for students to apply what they have learned and prepare themselves for industry needs. Therefore mining such projects gives insights of students’ experiences as well as industry project requirements and trends. In particular, we mine capstone projects executed by Information Systems students to discover patterns and insights related to people, organization, domain, industry needs and time. We build a capstone projects mining system (CPMS) based on classification models that leverage text mining, natural …

Multiple Instance Fuzzy Inference., Amine Ben Khalifa

Electronic Theses and Dissertations

A novel fuzzy learning framework that employs fuzzy inference to solve the problem of multiple instance learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Fuzzy Inference Systems (MI-FIS). Fuzzy inference is a powerful modeling framework that can handle computing with knowledge uncertainty and measurement imprecision effectively. Fuzzy Inference performs a non-linear mapping from an input space to an output space by deriving conclusions from a set of fuzzy if-then rules and known facts. Rules can be identified from expert knowledge, or learned from data. In multiple instance problems, the training data …

Facilitating Corpus Annotation By Improving Annotation Aggregation, Paul L. Felt

Theses and Dissertations

Annotated text corpora facilitate the linguistic investigation of language as well as the automation of natural language processing (NLP) tasks. NLP tasks include problems such as spam email detection, grammatical analysis, and identifying mentions of people, places, and events in text. However, constructing high quality annotated corpora can be expensive. Cost can be reduced by employing low-cost internet workers in a practice known as crowdsourcing, but the resulting annotations are often inaccurate, decreasing the usefulness of a corpus. This inaccuracy is typically mitigated by collecting multiple redundant judgments and aggregating them (e.g., via majority vote) to produce high quality consensus …

The Visual Framing Of The Three Cycles Of Climate Control In The New York Times 1851 To Present, Jason Lee Thompson

UNLV Theses, Dissertations, Professional Papers, and Capstones

This research explored the visual framing of climate control in The New York Times through three cycles of media history. Although no peer-reviewed study has explored this specific topic, a wealth of prior communication articles on both the visual and textual aspects of climate change and geoengineering in the media was mined in order to discover the frames present. Once the visual frames of climate control (war, fix, people, and impacts) were revealed a content analysis was conducted in order to see which frame elements were most and least frequent considering the images of climate control. When combining all three …

Modeling Social Media Content With Word Vectors For Recommendation, Ying Ding, Jing Jiang

Research Collection School Of Computing and Information Systems

In social media, recommender systems are becoming more and more important. Different techniques have been designed for recommendations under various scenarios, but many of them do not use user-generated content, which potentially reflects users’ opinions and interests. Although a few studies have tried to combine user-generated content with rating or adoption data, they mostly reply on lexical similarity to calculate textual similarity. However, in social media, a diverse range of words is used. This renders the traditional ways of calculating textual similarity ineffective. In this work, we apply vector representation of words to measure the semantic similarity between text. We …

Disjunctive Answer Set Solvers Via Templates, Remi Brochenin, Yuliya Lierler, Marco Maratea

Yuliya Lierler

Science Undergraduate Research Conference 2015 Booklet, Dublin Institute Of Technology, Institute Of Technology, Tallaght, Institute Of Technology, Blanchardstown

Group Reports

Dublin Institute of Technology (DIT), IT Tallaght and IT Blanchardstown hosted the Science Undergraduate Research Conference (SURC 2015) on 13th November 2015 in DIT's Grangegorman Campus. 25 students from DIT, IT Tallaght and IT Blanchardstown who completed an undergraduate research project in a Scientific discipline in the academic year 2014-15 presented at this conference.

The aims of the conference were to:

1. Provide current students with an opportunity to gain an understanding of the work which has been undertaken by recent graduates, and the career opportunities that exist for graduates in Scientific disciplines.
2. Provide recent graduates with an opportunity to gain …

Gis-Integrated Mathematical Modeling Of Social Phenomena At Macro- And Micro- Levels—A Multivariate Geographically-Weighted Regression Model For Identifying Locations Vulnerable To Hosting Terrorist Safe-Houses: France As Case Study, Elyktra Eisman

FIU Electronic Theses and Dissertations

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to …

Data Verifications For Online Social Networks, Mahmudur Rahman

FIU Electronic Theses and Dissertations

Social networks are popular platforms that simplify user interaction and encourage collaboration. They collect large amounts of media from their users, often reported from mobile devices. The value and impact of social media makes it however an attractive attack target. In this thesis, we focus on the following social media vulnerabilities. First, review centered social networks such as Yelp and Google Play have been shown to be the targets of significant search rank and malware proliferation attacks. Detecting fraudulent behaviors is thus paramount to prevent not only public opinion bias, but also to curb the distribution of malware. Second, the …

Exploiting Social Media Sources For Search, Fusion And Evaluation, Chia-Jung Lee

Doctoral Dissertations

The web contains heterogeneous information that is generated with different characteristics and is presented via different media. Social media, as one of the largest content carriers, has generated information from millions of users worldwide, creating material rapidly in all types of forms such as comments, images, tags, videos and ratings, etc. In social applications, the formation of online communities contributes to conversations of substantially broader aspects, as well as unfiltered opinions about subjects that are rarely covered in public media. Information accrued on social platforms, therefore, presents a unique opportunity to augment web sources such as Wikipedia or news pages, …

A Utility-Driven Approach To Supplier Evaluation And Selection: Empirical Validation Of An Integrated Solution Framework, Alptekin Ulutas, Nagesh Shukla, Senevi Kiridena, Peter Gibson

Nagesh Shukla

Supplier evaluation and selection (SES) problems have long been studied, leading to the development of a wide range of individual and hybrid models for solving them. However, the lack of widespread diffusion of existing SES models in the industry points to a need for simpler models that can systematically evaluate both qualitative and quantitative attributes of potential suppliers while enhancing the flexibility decision-makers need to account for relevant situational factors. Furthermore, empirical validations of existing models in SES have been few and far between. With a view to addressing these issues, this paper proposes an integrated solution framework that can …

Infinite-Noise Criticality: Nonequilibrium Phase Transitions In Fluctuating Environments, Thomas Vojta, José A. Hoyos

Physics Faculty Research & Creative Works

We study the effects of time-varying environmental noise on nonequilibrium phase transitions in spreading and growth processes. Using the examples of the logistic evolution equation as well as the contact process, we show that such temporal disorder gives rise to a distinct type of critical points at which the effective noise amplitude diverges on long time scales. This leads to enormous density fluctuations characterized by an infinitely broad probability distribution at criticality. We develop a real-time renormalization-group theory that provides a general framework for the effects of temporal disorder on nonequilibrium processes. We also discuss how general this exotic critical …

Data Selection Using Topic Adaptation For Statistical Machine Translation, Hitokazu Matsushita

Theses and Dissertations

Statistical machine translation (SMT) requires large quantities of bitexts (i.e., bilingual parallel corpora) as training data to yield good quality translations. While obtaining a large amount of training data is critical, the similarity between training and test data also has a significant impact on SMT performance. Many SMT studies define data similarity in terms of domain-overlap, and domains are defined to be synonymous with data sources. Consequently, the SMT community has focused on domain adaptation techniques that augment small (in-domain) datasets with large datasets from other sources (hence, out-of-domain, per the definition). However, many training datasets consist of topically diverse …

Interactive Machine Assistance: A Case Study In Linking Corpora And Dictionaries, Kevin P. Black

Theses and Dissertations

Machine learning can provide assistance to humans in making decisions, including linguistic decisions such as determining the part of speech of a word. Supervised machine learning methods derive patterns indicative of possible labels (decisions) from annotated example data. For many problems, including most language analysis problems, acquiring annotated data requires human annotators who are trained to understand the problem and to disambiguate among multiple possible labels. Hence, the availability of experts can limit the scope and quantity of annotated data. Machine-learned pre-annotation assistance, which suggests probable labels for unannotated items, can enable expert annotators to work more quickly and thus …

Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Social media has been a convenient platform for voicing opinions through posting messages, ranging from tweeting a short text to uploading a media file, or any combination of messages. Understanding the perceived emotions inherently underlying these user-generated contents (UGC) could bring light to emerging applications such as advertising and media analytics. Existing research efforts on affective computation are mostly dedicated to single media, either text captions or visual content. Few attempts for combined analysis of multiple media are made, despite that emotion can be viewed as an expression of multimodal experience. In this paper, we explore the learning of highly …

Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper presents an overview and comparative analysis of our systems designed for the TRECVID 2015 [1] multimedia event detection (MED) task. We submitted 17 runs, of which 5 each for the zeroexample, 10-example and 100-example subtasks for the Pre-Specified (PS) event detection and 2 runs for the 10-example subtask for the Ad-Hoc (AH) event detection. We did not participate in the Interactive Run. This year we focus on three different parts of the MED task: 1) extending the size of our concept bank and combining it with improved dense trajectories; 2) exploring strategies for semantic query generation (SQG); and …

Can You Summarize This? Identifying Correlates Of Input Difficulty For Generic Multi-Document Summarization, Ani Nenkova, Annie Louis

Ani Nenkova

Different summarization requirements could make the writing of a good summarymore difficult, or easier. Summary length and the characteristics of the input are such constraints influencing the quality of a potential summary. In this paper we report the results of a quantitative analysis on data from large-scale evaluations of multi-document summarization, empirically confirming this hypothesis. We further show that features measuring the cohesiveness of the input are highly correlated with eventual summary quality and that it is possible to use these as features to predict the difficulty of new, unseen, summarization inputs.

Automatic Sense Prediction For Implicit Discourse Relations In Text, Emily Pitler, Annie Louis, Ani Nenkova

Ani Nenkova

We present a series of experiments on automatically identifying the sense of implicit discourse relations, i.e. relations that are not marked with a discourse connective such as “but” or “because”. We work with a corpus of implicit relations present in newspaper text and report results on a test set that is representative of the naturally occurring distribution of senses. We use several linguistically informed features, including polarity tags, Levin verb classes, length of verb phrases, modality, context, and lexical features. In addition, we revisit past approaches using lexical pairs from unannotated text as features, explain some of their shortcomings and …

Automatic Evaluation Of Linguistic Quality In Multi-Document Summarization, Emily Pitler, Annie Louis, Ani Nenkova

Ani Nenkova

To date, few attempts have been made to develop and validate methods for automatic evaluation of linguistic quality in text summarization. We present the first systematic assessment of several diverse classes of metrics designed to capture various aspects of well-written text. We train and test linguistic quality models on consecutive years of NIST evaluation data in order to show the generality of results. For grammaticality, the best results come from a set of syntactic features. Focus, coherence and referential clarity are best evaluated by a class of features measuring local coherence on the basis of cosine similarity between sentences, coreference …

Structural Features For Predicting The Linguistic Quality Of Text: Applications To Machine Translation, Automatic Summarization And Human-Authored Text, Ani Nenkova, Jieun Chae, Annie Louis, Emily Pitler

Ani Nenkova

Sentence structure is considered to be an important component of the overall linguistic quality of text. Yet few empirical studies have sought to characterize how and to what extent structural features determine fluency and linguistic quality. We report the results of experiments on the predictive power of syntactic phrasing statistics and other structural features for these aspects of text. Manual assessments of sentence fluency for machine translation evaluation and text quality for summarization evaluation are used as gold-standard. We find that many structural features related to phrase length are weakly but significantly correlated with fluency and classifiers based on the …

Measuring Importance And Query Relevance In Toopic-Focused Multi-Document Summarization, Surabhi Gupta, Ani Nenkova, Dan Jurafsky

Ani Nenkova

The increasing complexity of summarization systems makes it difficult to analyze exactly which modules make a difference in performance. We carried out a principled comparison between the two most commonly used schemes for assigning importance to words in the context of query focused multi-document summarization: raw frequency (word probability) and log-likelihood ratio. We demonstrate that the advantages of log-likelihood ratio come from its known distributional properties which allow for the identification of a set of words that in its entirety defines the aboutness of the input. We also find that LLR is more suitable for query-focused summarization since, unlike raw …