Pablo Gervás

Computational Approaches to Storytelling and Creativity

This paper deals with computational approaches to storytelling, or the production of stories by computers, with a particular attention on the way human creativity is modelled or emulated, also in computational terms. Features relevant to creativity and to stories are analysed, and existing systems are reviewed under the light of that analysis. The extent to which they implement the key features proposed in recent models of computational creativity is discussed. Limitations, avenues of future research and expected trends are outlined.

An expert system for the composition of formal Spanish poetry

The present paper presents an application that composes formal poetry in Spanish in a semiautomatic interactive fashion. Automatic Spanish Poetry Expert and Rewriting Application (ASPERA) is a forward reasoning rule-based system that obtains from the user basic style parameters and an intended message; applies a knowledge-based pre-processor to select the most appropriate metric structure for the users wishes; and, by intelligent adaptation of selected examples from a corpus of verses, carries out a prose-to-poetry translation of the given message. In the composition process, ASPERA combines natural language generation and CBR techniques to apply a set of construction heuristics obtained from formal literature on Spanish poetry. If the user validates the poem draft presented by the system, the resulting verses are analysed and incorporated into the system data files.

Transferring Game Mastering Laws to Interactive Digital Storytelling

The Interactive Dilemma is the inevitable conflict between author’s determinism and interactor’s freedom. There are some approaches that try to tackle it, using strategies and heuristic rules that can combine on the fly the previously designed author material with the run-time decisions of the interactor. Interactive Narrative is a relatively new field and it is difficult to find formal studies that shows how to create this kind of art. Our proposal is based on the theoretical study of tabletop Role-Playing Games and it involves the practical implementation of those ideas for managing the interaction in a simple text adventure game. Game Masters are the best models we have found in real life for designing and directing interactive stories. In this paper we transfer their player modeling, their rules for interaction management and their improvising algorithms from the real world to a new Interactive Storytelling system.

User-model based personalized summarization

The potential of summary personalization is high, because a summary that would be useless to decide the relevance of a document if summarized in a generic manner, may be useful if the right sentences are selected that match the user interest. In this paper we defend the use of a personalized summarization facility to maximize the density of relevance of selections sent by a personalized information system to a given user. The personalization is applied to the digital newspaper domain and it used a user-model that stores long and short term interests using four reference systems: sections, categories, keywords and feedback terms. On the other side, it is crucial to measure how much information is lost during the summarization process, and how this information loss may affect the ability of the user to judge the relevance of a given document. The results obtained in two personalization systems show that personalized summaries perform better than generic and generic-personalized summaries in terms of identifying documents that satisfy user preferences. We also considered a user-centred direct evaluation that showed a high level of user satisfaction with the summaries.

Evaluation of Automatic Generation of Basic Stories

This paper presents an application that automatically generatesbasic stories: short texts that only narrate the main events of the plot. The system operates with a representation in Description Logics, combining stored fabulas with the narrative knowledge implemented in a domain-specific ontology. The domain of application is the traditional folk tale, using the well-known morphology of Vladimir Propp as narratological background. In order to evaluate the results, human judges blindly compared one of the generated basic stories to two alternatives: one rendered directly from a stored fabula of the knowledge base and another randomly generated. As a conclusion, possibilities of measuring the utility of the system in terms of quality and originality of the generated artifact are discussed.

A joint model of feature mining and sentiment analysis for product review rating

The information in customer reviews is of great interest to both companies and consumers. This information is usually presented as non-structured free-text so that automatically extracting and rating user opinions about a product is a challenging task. Moreover, this opinion highly depends on the product features on which the user judgments and impressions are expressed. Following this idea, our goal is to predict the overall rating of a product review based on the user opinion about the different product features that are evaluated in the review. To this end, the system first identifies the features that are relevant to consumers when evaluating a certain type of product, as well as the relative importance or salience of such features. The system then extracts from the review the user opinions about the different product features and quantifies such opinions. The salience of the different product features and the values that quantify the user opinions about them are used to construct a Vector of Feature Intensities which represents the review and will be the input to a machine learning model that classifies the review into different rating categories. Our method is evaluated over 1000 hotel reviews from booking.com. The results compare favorably with those achieved by other systems addressing similar evaluations.

Poetry Generation in COLIBRI

CBROnto is an ontology that incorporates common Case-Based Reasoning (CBR) terminology and serves as a domain-independent framework to design CBR applications. It is the core of COLIBRI, an environment to assist during the design of knowledge intensive CBR systems that combine cases with various knowledge types and reasoning methods. CBROnto captures knowledge about CBR tasks and methods, and aims to unify case specific and general domain knowledge representational needs. CBROnto specifies a modelling framework to describe reusable CBR Problem Solving Methods based on the CBR tasks they solve. This paper describes CBROntos main ideas and exemplifies them withan application to generate Spanishp oetry versions of texts provided by the user.

Concept-Graph Based Biomedical Automatic Summarization Using Ontologies

One of the main problems in research on automatic summarization is the inaccurate semantic interpretation of the source. Using specific domain knowledge can considerably alleviate the problem. In this paper, we introduce an ontology-based extractive method for summarization. It is based on mapping the text to concepts and representing the document and its sentences as graphs. We have applied our approach to summarize biomedical literature, taking advantages of free resources as UMLS. Preliminary empirical results are presented and pending problems are identified.

User-centred versus system-centred evaluation of a personalization system

Some of the most popular measures to evaluate information filtering systems are usually independent of the users because they are based in relevance judgments obtained from experts. On the other hand, the user-centred evaluation allows showing the different impressions that the users have perceived about the system running. This work is focused on discussing the problem of user-centred versus system-centred evaluation of a Web content personalization system where the personalization is based on a user model that stores long term (section, categories and keywords) and short term interests (adapted from user provided feedback). The user-centred evaluation is based on questionnaires filled in by the users before and after using the system and the system-centred evaluation is based on the comparison between ranking of documents, obtained from the application of a multi-tier selection process, and binary relevance judgments collected previously from real users. The user-centred and system-centred evaluations performed with 106 users during 14 working days have provided valuable data concerning the behaviour of the users with respect to issues such as document relevance or the relative importance attributed to different ways of personalization. The results obtained shows general satisfaction on both the personalization processes (selection, adaptation and presentation) and the system as a whole.

One Half or 50%? An Eye-Tracking Study of Number Representation Readability

Are numbers expressed as digits easier to read and understand than written with letters? What about fractions and percentages? Exact or rounded values? We present an eye-tracking study that attempts to answer these questions for Spanish, using fixation and reading time to measure readability as well as comprehension questions to score understandability. We find that digits are faster to read but do not help comprehension. Fractions help understandability while percentages help readability. No significant results were found concerning the influence of rounding. Our experiments were performed by 72 persons, half of them with dyslexia. To the best of our knowledge, this is the first study that addresses the cognitive load of number representation in any language, even more for people with dyslexia.