Physical Sciences and Mathematics Commons^™

Novel Primitive Decompositions For Real-World Physical Reasoning, Mackie Zhoou, Bridget Duah, Jamie C. Macbeth

Computer Science: Faculty Publications

In this work, we are concerned with developing cognitive representations that may en- hance the ability for self-supervised learning systems to learn language as part of their world explorations. We apply insights from in-depth language understanding systems to the problem, specifically representations which decompose language inputs into language-free structures that are complex combinations of primitives representing cognitive abstractions such as object permanence, movement, and spatial relationships. These decompositions, performed by a system traditionally called a conceptual analyzer, link words with complex non-linguistic structures that engender the rich relations between language expressions and world exploration that are a familiar aspect of …

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti

Browse all Theses and Dissertations

Conversations are more than just a sequence of text, it is where two or more participants interact in order to achieve their goals. Conversation Understanding (CU) requires all participants to understand each others intent. In the past decade, CU has been extended from automated human-human text processing to build automated conversational agents for human-machine interactions. Despite their popularity, these automated conversational agents (like Siri, Alexa, etc) can't handle more than one or two utterances, and they don't recognize conversations as intents. The development of approaches that extract intents behind an utterance is essential for the advancements of Question Answering (QA) …

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti

Browse all Theses and Dissertations

Conversations are more than just a sequence of text, it is where two or more participants interact in order to achieve their goals. Conversation Understanding (CU) requires all participants to understand each others intent. In the past decade, CU has been extended from automated human-human text processing to build automated conversational agents for human-machine interactions. Despite their popularity, these automated conversational agents (like Siri, Alexa, etc) can't handle more than one or two utterances, and they don't recognize conversations as intents. The development of approaches that extract intents behind an utterance is essential for the advancements of Question Answering (QA) …

Tree-Augmented Cross-Modal Encoding For Complex-Query Video Retrieval, Xun Yang, Jianfeng Dong, Yixin Cao, Xun Wang, Meng Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The rapid growth of user-generated videos on the Internet has intensified the need for text-based video retrieval systems. Traditional methods mainly favor the concept-based paradigm on retrieval with simple queries, which are usually ineffective for complex queries that carry far more complex semantics. Recently, embedding-based paradigm has emerged as a popular approach. It aims to map the queries and videos into a shared embedding space where semantically-similar texts and videos are much closer to each other. Despite its simplicity, it forgoes the exploitation of the syntactic structure of text queries, making it suboptimal to model the complex queries. To facilitate …

Automatic Conversation Review For Intelligent Virtual Assistants, Ian R. Beaver

Computer Science ETDs

When reviewing the performance of Intelligent Virtual Assistants (IVAs), it is desirable to prioritize conversations involving misunderstood human inputs. These conversations uncover error in natural language understanding and help prioritize and expedite improvements to the IVA. As human reviewer time is valuable and manual analysis is time consuming, prioritizing the conversations where misunderstanding has likely occurred reduces costs and speeds improvement. A system for measuring the posthoc risk of missed intent associated with a single human input is presented. Numerous indicators of risk are explored and implemented. These indicators are combined using various means and evaluated on real world data. …

Al Planning Assistant For Scheduling Daily Activities, Priyanka Ahuja

Theses and Dissertations

Artificial conversational agents are software agents that can interact with humans in the way humans do. Siri Cortana, and Alexa are examples of intelligent agents that can help us with almost all the basic tasks. These agents are smart enough to do the basic tasks, but not as much when it comes to complex tasks, such as analyzing traffic data, reviewing scheduling conflicts, rescheduling meetings while resolving conflicts, and offering suggestions based upon data analyses (e.g. traffic patterns, weather, etc.) The actual potential of dialogue-based task agent potential remains untapped. The reason is the fact agents lack the ability to …

A Framework To Understand Emoji Meaning: Similarity And Sense Disambiguation Of Emoji Using Emojinet, Sanjaya Wijeratne

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Pictographs, commonly referred to as `emoji’, have become a popular way to enhance electronic communications. They are an important component of the language used in social media. With their introduction in the late 1990’s, emoji have been widely used to enhance the sentiment, emotion, and sarcasm expressed in social media messages. They are equally popular across many social media sites including Facebook, Instagram, and Twitter. In 2015, Instagram reported that nearly half of the photo comments posted on Instagram contain emoji, and in the same year, Twitter reported that the `face with tears of joy’ emoji has been tweeted 6.6 …

Nlu Framework For Voice Enabling Non-Native Applications On Smart Devices, Soujanya Lanka, Deepika Panthania, Pooja Kushalappa, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Voice is a critical user interface on smart devices (wearables, phones, speakers, televisions) to access applications (or services) available on them. Unfortunately, only a few native applications (provided by the OS developer) are typically voice enabled in devices of today. Since, the utility of a smart device is determined more by the strength of external applications developed for the device, voice enabling non-native applications in a scalable, seamless manner within the device is a critical use case and is the focus of our work. We have developed a Natural Language Understanding (NLU) framework that uses templates supported by the application …

Prepositional Phrase Attachment Problem Revisited: How Verbnet Can Help, Dan Bailey, Yuliya Lierler, Benjamin Susman

Yuliya Lierler

The Winograd Schema Challenge And Reasoning About Correlation, Dan Bailey, Amelia Harrison, Yuliya Lierler, Vladimir Lifschitz, Julian Michael

Yuliya Lierler

Aspccgtk: Towards Syntactic Parsing With Semantic Disambiguation, Yuliya Lierler, Peter Schueller

Yuliya Lierler

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

Yuliya Lierler

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.

Research Challenges And Opportunities In Knowledge Representation, Section 2.3.2: Applications Based On Formal Models, Natasha Noy, Deborah Mcguinness, Yuliya Lierler

Yuliya Lierler

Final report edited by Natasha Noy and Deborah McGuinness. Report Section 2.3.2, Applications based on formal models, authored by Yuliya Lierer, UNO faculty member.

Parsing Combinatory Categorial Grammar With Answer Set Programming: Preliminary Report, Yuliya Lierler, Peter Schüller

Yuliya Lierler

Combinatory categorial grammar (CCG) is a grammar formalism used for natural language parsing. CCG assigns structured lexical categories to words and uses a small set of combinatory rules to combine these categories to parse a sentence. In this work we propose and implement a new approach to CCG parsing that relies on a prominent knowledge representation formalism, answer set programming (ASP) — a declarative programming paradigm. We formulate the task of CCG parsing as a planning problem and use an ASP computational tool to compute solutions that correspond to valid parses. Compared to other approaches, there is no need to …

Logic Programs Vs. First-Order Formulas In Textual Inference, Yuliya Lierler, Vladimir Lifschitz

Yuliya Lierler

In the problem of recognizing textual entailment, the goal is to decide, given a text and a hypothesis expressed in a natural language, whether a human reasoner would call the hypothesis a consequence of the text. One approach to this problem is to use a first-order reasoning tool to check whether the hypothesis can be derived from the text conjoined with relevant background knowledge, after expressing all of them by first-order formulas. Another possibility is to express the hypothesis, the text, and the background knowledge in a logic programming language, and use a logic programming system. We discuss the relation …

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

Yuliya Lierler

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.

Natural Language Document And Event Association Using Stochastic Petri Net Modeling, Michael Thomas Mills

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The purpose of this research is to design and implement a new methodology that captures the natural language understanding of events from English natural language text and model it using Stochastic Petri Nets. To establish a baseline of recent natural language processing (NLP) and understanding (NLU) research, two surveys are presented. One is a general survey in NLP and NLU methodologies for processing multi-documents. It summarizes and presents methodologies in terms of their features, capabilities, and maturity. The second survey focuses on graph-based methods for NL text processing and understanding and analyzes them in terms of their functional descriptions, capabilities …

Parsing Combinatory Categorial Grammar Via Planning In Answer Set Programming, Yuliya Lierler, Peter Schueller

Yuliya Lierler