Computer Sciences Commons^™

Practical Cost-Conscious Active Learning For Data Annotation In Annotator-Initiated Environments, Robbie A. Haertel

Theses and Dissertations

Many projects exist whose purpose is to augment raw data with annotations that increase the usefulness of the data. The number of these projects is rapidly growing and in the age of “big data” the amount of data to be annotated is likewise growing within each project. One common use of such data is in supervised machine learning, which requires labeled data to train a predictive model. Annotation is often a very expensive proposition, particularly for structured data. The purpose of this dissertation is to explore methods of reducing the cost of creating such data sets, including annotated text corpora.We …

Misheard Me Oronyminator: Using Oronyms To Validate The Correctness Of Frequency Dictionaries, Jennifer G. Hughes

Master's Theses

In the field of speech recognition, an algorithm must learn to tell the difference between "a nice rock" and "a gneiss rock". These identical-sounding phrases are called oronyms. Word frequency dictionaries are often used by speech recognition systems to help resolve phonetic sequences with more than one possible orthographic phrase interpretation, by looking up which oronym of the root phonetic sequence contains the most-common words.

Our paper demonstrates a technique used to validate word frequency dictionary values. We chose to use frequency values from the UNISYN dictionary, which tallies each word on a per-occurance basis, using a proprietary text corpus, …

Towards A Tight Integration Of Syntactic Parsing With Semantic Disambiguation By Means Of Declarative Programming, Yuliya Lierler, Peter Schüller

Computer Science Faculty Proceedings & Presentations

We propose and advocate the use of an advanced declarative programming paradigm – answer set programming – as a uniform platform for integrated approach towards syntax-semantic processing in natural language. We illustrate that (a) the parsing technology based on answer set programming implementation reaches performance sufficient for being a useful NLP tool, and (b) the proposed method for incorporating semantic information from FRAMENET into syntactic parsing may prove to be useful in allowing semantic-based disambiguation of syntactic structures.

Automatically Acquiring A Semantic Network Of Related Concepts, Sean Szumlanski

Electronic Theses and Dissertations

We describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to automatically disambiguate them to their corresponding WordNet noun senses (i.e., concepts). The resultant concept-to-concept associations, stemming from 7,593 target nouns, with 17,104 distinct senses among them, constitute a large-scale semantic …

Text-Based Phishing Detection Using A Simulation Model, Gilchan Park

Open Access Theses

Phishing is one of the most potentially disruptive actions that can be performed on the Internet. Intellectual property and other pertinent business information could potentially be at risk if a user falls for a phishing attack. The most common way of carrying out a phishing attack is through email. The adversary sends an email with a link to a fraudulent site to lure consumers into divulging their confidential information. While such attacks may be easily identifiable for those well-versed in technology, it may be difficult for the typical Internet user to spot a fraudulent email.

The emphasis of this research …

Toward Digitizing The Human Experience : A New Resource For Natural Language Processing, Jerry Scott Weltman

LSU Doctoral Dissertations

A long-standing goal of Artificial Intelligence is to program computers that understand natural language. A basic obstacle is that computers lack the common sense that even small children acquire simply by experiencing life, and no one has devised a way to program this experience into a computer. This dissertation presents a methodology and proof-of-concept software system that enables non-experts, with some training, to create simple experiences. For the purposes of this dissertation, an experience is a series of time-ordered comic frames, annotated with the changing intentional and physical states of the characters and objects in each frame. Each frame represents …

Artificial Intelligence – I: A Preliminary Framework For Human-Agent Communication In Electronic Negotiations, Moez Ur Rehman, Nosheen Riaz

International Conference on Information and Communication Technologies

Electronic negotiations are business negotiations conducted via electronic means using information and communications technologies (ICT). Two dominant types of electronic negotiation systems are automated negotiation systems for software agents and negotiation support systems (NSSs) for humans. However, the integration of two types for human-agent negotiations is an important task. In this paper, an extended communication model for human-agent business negotiations is presented. For this purpose, the underlying communication models of automated negotiations and NSSs are analyzed. The extended communication model is based on a common negotiation ontology which captures the negotiation agenda and paves the way for such hybrid communication, …

Automatic Knowledge Extraction For Filling In Biography Forms From Turkish Texts, İlknur Pehli̇van, Zeynep Orhan

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a method for building an automatic knowledge extraction system for filling in biography forms from Turkish texts. Several biographies are analyzed in order to choose the set of biography categories to be studied. The fields of the biography form to be created are also defined based on this analysis. Information extraction techniques are used for implementation. A separate testing platform is designed to evaluate the accuracy of the extracted data. Results of the testing platform have shown this study to be a promising process to be further developed especially for creating forms in the Turkish language.

Text Summarization Using Concept Hierarchy, Xiaomei Huang

Doctoral Dissertations

This dissertation aims to create new sentences to summarize text documents. In addition to generating new sentences, this project also generates new concepts and extracts key sentences to summarize documents. This project is the first research work that can generate new key concepts and can create new sentences to summarize documents.

Automatic document summarization is the process of creating a condensed version of the document. The condensed version extracts the key contents from the original document. Most related research uses statistical methods that generate a summary based on word distribution in the document. In this dissertation, we create a summary …

Natural Language Processing And E-Government: Crime Information Extraction From Heterogeneous Data Sources, Chih Hao Ku '12, Alicia Iriberri '06, Gondy Leroy

CGU Faculty Publications and Research

Much information that could help solve and prevent crimes is never gathered because the reporting methods available to citizens and law enforcement personnel are not optimal. Detectives do not have sufficient time to interview crime victims and witnesses. Moreover, many victims and witnesses are too scared or embarrassed to report incidents. We are developing an interviewing system that will help collect such information. We report here on one component, the crime information extraction module, which uses natural language processing to extract crime information from police reports, newspaper articles, and victims’ and witnesses’ crime narratives. We tested our approach with two …

Mobile Semantic Computing, Karthik Gomadam, Anupam Joshi, Amit P. Sheth

Kno.e.sis Publications

We propose to organize a special session on research in the intersection of mobile computing, the Semantic Web and Web services.

This session will examine how the research in these areas can serve as a foundation for new architectural and communication paradigms that can enhance service creation, distribution, discovery, integration and utilization in distributed and ubiquitous environments. Some of the initial areas that our early research have highlighted are :

1. Semantic annotation of data in bandwidth constrained environments such as mobile networks to promote efficient bandwidth utilization
2. Possibilities of using microformats such as RDFa and opportunities that can be explored …

Medical Language Processing For Patient Diagnosis Using Text Classification And Negation Labelling, Brian Mac Namee, John D. Kelleher, Sarah Jane Delany

Conference papers

This paper describes the approach of the DIT AIGroup to the i2b2 Obesity Challenge to build a system to diagnose obesity and related co-morbidities from narrative, unstructured patient records. Based on experimental results a system was developed which used knowledge-light text classification using decision trees, and negation labelling.

Generating Paraphrases With Greater Variation Using Syntactic Phrases, Rebecca Diane Madsen

Theses and Dissertations

Given a sentence, a paraphrase generation system produces a sentence that says the same thing but usually in a different way. The paraphrase generation problem can be formulated in the machine translation paradigm; instead of translation of English to a foreign language, the system translates an English sentence (for example) to another English sentence. Quirk et al. (2004) demonstrated this approach to generate almost 90% acceptable paraphrases. However, most of the sentences had little variation from the original input sentence. Leveraging syntactic information, this thesis project presents an approach that successfully generated more varied paraphrase sentences than the approach of …

Surface Realization Using A Featurized Syntactic Statistical Language Model, Thomas L. Packer

Theses and Dissertations

An important challenge in natural language surface realization is the generation of grammatical sentences from incomplete sentence plans. Realization can be broken into a two-stage process consisting of an over-generating rule-based module followed by a ranker that outputs the most probable candidate sentence based on a statistical language model. Thus far, an n-gram language model has been evaluated in this context. More sophisticated syntactic knowledge is expected to improve such a ranker. In this thesis, a new language model based on featurized functional dependency syntax was developed and evaluated. Generation accuracies and cross-entropy for the new language model did not …

Model Generation For Generalized Quantifiers Via Answer Set Programming, Yuliya Lierler, Günther Görz

Computer Science Faculty Proceedings & Presentations

For the semantic evaluation of natural language sentences, in particular those containing generalized quantifiers, we subscribe to the generate and test methodology to produce models of such sentences. These models are considered as means by which the sentences can be interpreted within a natural language processing system. The goal of this paper is to demonstrate that answer set programming is a simple, efficient and particularly well suited model generation technique for this purpose, leading to a straightforward implementation.

Syntax-Based Concept Extraction For Question Answering, Demetrios Glinos

Electronic Theses and Dissertations

Question answering (QA) stands squarely along the path from document retrieval to text understanding. As an area of research interest, it serves as a proving ground where strategies for document processing, knowledge representation, question analysis, and answer extraction may be evaluated in real world information extraction contexts. The task is to go beyond the representation of text documents as "bags of words" or data blobs that can be scanned for keyword combinations and word collocations in the manner of internet search engines. Instead, the goal is to recognize and extract the semantic content of the text, and to organize it …

A Dynamic Weight Assignment Approach For Ir Systems, M. Shoaib, Prof Dr. Abad Ali Shah, A. Vashishta

International Conference on Information and Communication Technologies

Weights are assigned to the extracted keywords for partial matching and computing ranking in an IR system. Weight assignment technique is suggested by the IR model that is used for an IR system. Currently suggested weight assignment techniques are static which means that once weight is assigned a keyword it remains unchanged during life-span of an IR system. In this paper, we suggest a dynamic weight assignment technique. This technique can be used by any IR model that supports partial matching.

Non-Linear And Linear Transformations Of Features For Robust Speech Recognition And Speaker Identification, Saurabh Prasad

Electrical & Computer Engineering Theses & Dissertations

Automatic speech recognizers perform poorly when training and test data are systematically different in terms of noise and channel characteristics. One manifestation of such differences is variations in the probability density functions (pdfs) between training and test features. Consequently, both automatic speech recognition and automatic speaker identification may be severely degraded. Previous attempts to mm1m1ze this problem include Cepstral Mean and Variance Normalization and transforming all speech features to a uni-variate Gaussian pdf. In this thesis, two techniques are presented for non-linearly scaling speech features to fit them to a target pdf - the first is based on the principles …

Computing Answer Sets Of A Logic Program Via-Enumeration Of Sat Certificates, Yuliya Lierler, Marco Maratea

Computer Science Faculty Proceedings & Presentations

Answer set programming is a new programming paradigm proposed based on the answer set semantics of Prolog. It is well known that an answer set for a logic program is also a model of the program's completion. The converse is true when the logic program is "tight". Lin and Zhao showed that for non-tight programs the models of completion which do not correspond to answer sets can be eliminated by adding to the completion what they called "loop formulas". Nevertheless, their solver ASSAT 1 has some disadvantages: it can work only with basic rules, and it can compute only one …

Experience-Based Language Acquisition: A Computational Model Of Human Language Acquisition, Brian Edward Pangburn

LSU Doctoral Dissertations

Almost from the very beginning of the digital age, people have sought better ways to communicate with computers. This research investigates how computers might be enabled to understand natural language in a more humanlike way. Based, in part, on cognitive development in infants, we introduce an open computational framework for visual perception and grounded language acquisition called Experience-Based Language Acquisition (EBLA). EBLA can “watch” a series of short videos and acquire a simple language of nouns and verbs corresponding to the objects and object-object relations in those videos. Upon acquiring this protolanguage, EBLA can perform basic scene analysis to generate …

Meeting Medical Terminology Needs: The Ontology-Enhanced Medical Concept Mapper, Gondy Leroy, Hsinchun Chen

CGU Faculty Publications and Research

This paper describes the development and testing of the Medical Concept Mapper, a tool designed to facilitate access to online medical information sources by providing users with appropriate medical search terms for their personal queries. Our system is valuable for patients whose knowledge of medical vocabularies is inadequate to find the desired information, and for medical experts who search for information outside their field of expertise. The Medical Concept Mapper maps synonyms and semantically related concepts to a user's query. The system is unique because it integrates our natural language processing tool, i.e., the Arizona (AZ) Noun Phraser, with human-created …

Ilona: An Advanced Cai Tutorial System For The Fundamentals Of Logic, Otto Mayer, Graham E. Oberem, Fillia Makedon

Computer Science Technical Reports

An advanced tutorial system for teaching the fundamentals of logic has been developed to run on UNIX work stations and commonly available micro-computers. An important part of this tutorial is the intelligent problem solving environment which allows students to practise wiriting logical sentences in mathematical notation. A natural language system for intelligent logic narrative analysis (ILONA) allows students to type in their own logical sentences in plain English and then have the computer check their working when they write these in mathematical form. ILONA is an intelligent tutoring system which allows students a great deal of initiative in problem solving …

Artificial Intelligence: Myths And Realities, Hugo D'Alarcao

Bridgewater Review

Artificial intelligence the name conjures images of mechanical monsters, the Golem, Dr. Frankenstein’s creation and the rebellious computer Hal. We have always been fascinated by the possibility of creating a machine in our image, but this fascination is often accompanied by apprehension. We fear losing control of our creation and suspect that it might turn against us. It is this duality, this conflict between the desire to create and the fear of the consequences of the creation that has been so successfully exploited by writers. It is also, in part, this fascination that has recently brought the field of Artificial …