Narrative Information Extraction with Non-Linear Natural Language Processing Pipelines

Computational narrative focuses on methods to algorithmically analyze, model, and generate narratives. Most current work in story generation, drama management or even literature analysis relies on manually authoring domain knowledge in some specific formal representation language, which is expensive to generate. In this dissertation we explore how to automatically extract narrative information from unannotated natural language text, how to evaluate the extraction process, how to improve the extraction process, and how to use the extracted information in story generation applications. As our application domain, we use Vladimir Propp's narrative theory and the corresponding Russian and Slavic folktales as our corpus. Our hypothesis is that incorporating narrative-level domain knowledge (i.e., Proppian theory) to core natural language processing (NLP) and information extraction can improve the performance of tasks (such as coreference resolution), and the extracted narrative information. We devised a non-linear information extraction pipeline framework which we implemented in Voz, our narrative information extraction system. Finally, we studied how to map the output of Voz to an intermediate computational narrative model and use it as input for an existing story generation system, thus further connecting existing work in NLP and computational narrative. As far as we know, it is the first end-to-end computational narrative system that can automatically process a corpus of unannotated natural language stories, extract explicit domain knowledge from them, and use it to generate new stories. Our user study results show that specific error introduced during the information extraction process can be mitigated downstream and have virtually no effect on the perceived quality of the generated stories compared to generating stories using handcrafted domain knowledge.Ph.D., Computer Science -- Drexel University, 201

Parser of emotion metaphors

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 1999.Includes bibliographical references (leaves 77-80).Although metaphor is generally recognized as an integral component of everyday language, very few computational systems capable of understanding metaphoric utterances exist today. This thesis describes one approach to the problem and presents PoEM, a prototype system which recognizes and interprets metaphoric descriptions of emotions and mental states in single-sentence input. Building upon previous work in knowledge-based metaphor comprehension, this research adopts a goal-driven approach which assumes each metaphor is selected by a speaker for its aptness at serving a particular communicative goal. To identify these goals, an empirical analysis of metaphor distribution in song lyrics was performed, and typical communicative intentions and surface patterns were identified for the top five most frequently occurring metaphor groups. These intentions and surface patterns have been implemented as a set of metaphor templates and interpretation rules in PoEM, using the WordNet lexical database for supplemental semantic information. Evaluation of PoEM demonstrates fairly high accuracy but low recall.Laurie Satsue Hiyakumoto.S.M

Nanooptics with surface plasmons and resonant nanoparticles

[no abstract

Personalization Paradox in Behavior Change Apps:Lessons from a Social Comparison-Based Personalized App for Physical Activity

Social comparison-based features are widely used in social computing apps. However, most existing apps are not grounded in social comparison theories and do not consider individual differences in social comparison preferences and reactions. This paper is among the first to automatically personalize social comparison targets. In the context of an m-health app for physical activity, we use artificial intelligence (AI) techniques of multi-armed bandits. Results from our user study (n=53) indicate that there is some evidence that motivation can be increased using the AI-based personalization of social comparison. The detected effects achieved small-to-moderate effect sizes, illustrating the real-world implications of the intervention for enhancing motivation and physical activity. In addition to design implications for social comparison features in social apps, this paper identified the personalization paradox, the conflict between user modeling and adaptation, as a key design challenge of personalized applications for behavior change. Additionally, we propose research directions to mitigate this Personalization Paradox

Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application

This thesis proposes SPECS: a Standardised Procedure for Evaluating Creative Systems. No methodology has been accepted as standard for evaluating the creativity of a system in the field of computational creativity and the multi-faceted and subjective nature of creativity generates substantial definitional issues. Evaluative practice has developed a general lack of rigour and systematicity, hindering research progress. SPECS is a standardised and systematic methodology for evaluating computational creativity. It is flexible enough to be applied to a variety of different types of creative system and adaptable to specific demands in different types of creativity. In the three-stage process of evaluation, researchers are required to be specific about what creativity entails in the domain they work in and what standards they test a system’s creativity by. To assist researchers, definitional issues are investigated and a set of components representing aspects of creativity is presented, which was empirically derived using computational linguistics analysis. These components are recommended for use within SPECS, being offered as a general definition of creativity that can be customised to account for any specific priorities for creativity in a given domain. SPECS is applied in a case study for detailed comparisons of the creativity of three musical improvisation systems, identifying which systems are more creative than others and why. In a second case study, SPECS is used to capture initial impressions on the creativity of systems presented at a 2011 computational creativity research event. Five systems performing different creative tasks are compared and contrasted. These case studies exemplify the valuable information that can be obtained on a system’s strengths and weaknesses. SPECS gives researchers vital feedback for improving their systems’ creativity, informing further progress in computational creativity research

A Contextual Approach to Real Time, Interactive Narrative Generation

Oral story telling has become a lost art of family histories because social media and technology have taken over the personal interactions that once passed on the important stories and facts from generation to generation. This dissertation presents and evaluates a method of generating a narrative with input from the listener without actually forcing him or her to become an actual character in the narrative. This system is called CAMPFIRE Story Telling System (STS) and employs a contextual approach to story generation. This system uses the Cooperating Context Method (CCM) to generate and tell dynamic stories in real time and can be modified by the listener. CCM was created to overcome the weaknesses found in other contextual approaches during story generation while still meeting the design criteria of 1) being able to plan out a story; 2) being able to create a narrative that is entertaining to the listener; and 3) being able to modify the story that could incorporate the listener\u27s request in the story. The CCM process begins by creating a list of tasks by analyzing the current situation. A list of contexts is narrowed down through a series of algorithms into two lists: high priority and low priority lists. These lists are analyzed and a set of context best suited to handle the tasks are selected. The CAMPFIRE STS was rigorously assessed for its functionality, novelty, and user acceptance as well as the time needed to modify the knowledge base. These evaluations showed that the CAMPFIRE STS has the ability to create novel stories using the same knowledge base. A group of 38 test subjects used and evaluated CAMPFIRE STS with respect to its use for children, story entertainment, story creativity and the system\u27s ease of use answering a extensive survey of 54 questions. The survey showed that CAMPFIRE STS can create stories appropriate for bedtime stories with some minor modifications and that the generated stories are novel and entertaining stories, and that it was an easy system to use

Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application

This thesis proposes SPECS: a Standardised Procedure for Evaluating Creative Systems. No methodology has been accepted as standard for evaluating the creativity of a system in the field of computational creativity and the multi-faceted and subjective nature of creativity generates substantial definitional issues. Evaluative practice has developed a general lack of rigour and systematicity, hindering research progress. SPECS is a standardised and systematic methodology for evaluating computational creativity. It is flexible enough to be applied to a variety of different types of creative system and adaptable to specific demands in different types of creativity. In the three-stage process of evaluation, researchers are required to be specific about what creativity entails in the domain they work in and what standards they test a system’s creativity by. To assist researchers, definitional issues are investigated and a set of components representing aspects of creativity is presented, which was empirically derived using computational linguistics analysis. These components are recommended for use within SPECS, being offered as a general definition of creativity that can be customised to account for any specific priorities for creativity in a given domain. SPECS is applied in a case study for detailed comparisons of the creativity of three musical improvisation systems, identifying which systems are more creative than others and why. In a second case study, SPECS is used to capture initial impressions on the creativity of systems presented at a 2011 computational creativity research event. Five systems performing different creative tasks are compared and contrasted. These case studies exemplify the valuable information that can be obtained on a system’s strengths and weaknesses. SPECS gives researchers vital feedback for improving their systems’ creativity, informing further progress in computational creativity research

Simulated role-playing from crowdsourced data

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 173-178).Collective Artificial Intelligence (CAl) simulates human intelligence from data contributed by many humans, mined for inter-related patterns. This thesis applies CAI to social role-playing, introducing an end-to-end process for compositing recorded performances from thousands of humans, and simulating open-ended interaction from this data. The CAI process combines crowdsourcing, pattern discovery, and case-based planning. Content creation is crowdsourced by recording role-players online. Browser-based tools allow nonexperts to annotate data, organizing content into a hierarchical narrative structure. Patterns discovered from data power a novel system combining plan recognition with case-based planning. The combination of this process and structure produces a new medium, which exploits a massive corpus to realize characters who interact and converse with humans. This medium enables new experiences in videogames, and new classes of training simulations, therapeutic applications, and social robots. While advances in graphics support incredible freedom to interact physically in simulations, current approaches to development restrict simulated social interaction to hand-crafted branches that do not scale to the thousands of possible patterns of actions and utterances observed in actual human interaction. There is a tension between freedom and system comprehension due to two bottlenecks, making open-ended social interaction a challenge. First is the authorial effort entailed to cover all possible inputs. Second, like other cognitive processes, imagination is a bounded resource. Any individual author only has so much imagination. The convergence of advances in connectivity, storage, and processing power is bringing people together in ways never before possible, amplifying the imagination of individuals by harnessing the creativity and productivity of the crowd, revolutionizing how we create media, and what media we can create. By embracing data-driven approaches, and capitalizing on the creativity of the crowd, authoring bottlenecks can be overcome, taking a step toward realizing a medium that robustly supports player choice. Doing so requires rethinking both technology and division of labor in media production. As a proof of concept, a CAI system has been evaluated by recording over 10,000 performances in The Restaurant Game, automating an Al-controlled waitress who interacts in the world, and converses with a human via text or speech. Quantitative results demonstrate how CAI supports significantly more open-ended interaction with humans, while focus groups reveal factors for improving engagement.by Jeffrey David Orkin.Ph.D

Some theory and phenomenology of neutrino masses and the baryon asymmetry

This thesis provides some theoretical and phenomenological work on two of the outstanding problems in modern physics, namely, the extreme smallness of neutrino masses and the relative abundance of matter over antimatter. A theorem is developed relating the smallness of the light neutrino masses to the degree of lepton number violation in some seesaw extensions of the Standard Model of particle physics. It is shown that for exactly massless light neutrinos there must be an exact lepton number symmetry. Then the viability of thermal leptogenesis as a resolution to the baryon asymmetry problem at different scales is assessed using more sophisticated numerical tools than have previously been applied. It is shown that, if fine-tuned solutions are allowed, the scale may be lowered to $\sim 10^6$ GeV. Using these results, it is shown that, if CP violation comes purely from the phases of the PMNS matrix, thermal leptogenesis may still be viable over a range of scales covering $10^6$ --- $10^{13}$ GeV. It is also shown that thermal leptogenesis is viable in the Neutrino Option, in which the Higgs potential has its dimensionful parameter provided by loop corrections from the heavy Majorana neutrinos in the type I seesaw at a mass scale $\sim 10^6$ GeV