A model and an algebra for semi-structured and full-text queries

The need for a convergence between semi-structured data management and Information Retrieval techniques is manifest to the scientific community. In order to fulfil this growing request, W3C has recently proposed XQuery Full Text, an IR-oriented extension of XQuery. However, the issue of query optimization requires the study of important properties like query equivalence and containment; to this aim, a formal representation of document and queries is needed. The goal of this thesis is to establish such formal background. We define a data model for XML documents and propose an algebra able to represent most of XQuery Full-Text expressions. We show how an XQuery Full-Text expression can be translated into an algebraic expression and how an algebraic expression can be optimized.

Testo e memoria tra semiotica e scienze cognitive: una situazione sperimentale intorno al ricordo di un film

The research project presented in this dissertation is about text and memory. The title of the work is "Text and memory between Semiotics and Cognitive Science: an experimental setting about remembering a movie". The object of the research is the relationship between texts or "textuality" - using a more general semiotic term - and memory. The goal is to analyze the link between those semiotic artifacts that a culture defines as autonomous meaningful objects - namely texts - and the cognitive performance of memory that allows to remember them. An active dialogue between Semiotics and Cognitive Science is the theoretical paradigm in which this research is set, the major intend is to establish a productive alignment between the "theory of text" developed in Semiotics and the "theory of memory" outlined in Cognitive Science. In particular the research is an attempt to study how human subjects remember and/or misremember a film, as a specific case study; in semiotics, films are “cinematographic texts”. The research is based on the production of a corpus of data gained through the qualitative method of interviewing. After an initial screening of a fulllength feature film each participant of the experiment has been interviewed twice, according to a pre-established set of questions. The first interview immediately after the screening: the subsequent, follow-up interview three months from screening. The purpose of this design is to elicit two types of recall from the participants. In order to conduce a comparative inquiry, three films have been used in the experimental setting. Each film has been watched by thirteen subjects, that have been interviewed twice. The corpus of data is then made by seventy-eight interviews. The present dissertation displays the results of the investigation of these interviews. It is divided into six main parts. Chapter one presents a theoretical framework about the two main issues: memory and text. The issue of the memory is introduced through many recherches drown up in the field of Cognitive Science and Neuroscience. It is developed, at the same time, a possible relationship with a semiotic approach. The theoretical debate about textuality, characterizing the field of Semiotics, is examined in the same chapter. Chapter two deals with methodology, showing the process of definition of the whole method used for production of the corpus of data. The interview is explored in detail: how it is born, what are the expected results, what are the main underlying hypothesis. In Chapter three the investigation of the answers given by the spectators starts. It is examined the phenomenon of the outstanding details of the process of remembering, trying to define them in a semiotic way. Moreover there is an investigation of the most remembered scenes in the movie. Chapter four considers how the spectators deal with the whole narrative. At the same time it is examined what they think about the global meaning of the film. Chapter five is about affects. It tries to define the role of emotions in the process of comprehension and remembering. Chapter six presents a study of how the spectators account for a single scene of the movie. The complete work offers a broad perspective about the semiotic issue of textuality, using both a semiotic competence and a cognitive one. At the same time it presents a new outlook on the issue of memory, opening several direction of research.

Liquid crystal polymer brushes and their application as alignment layers in liquid crystal cells

Liquid Crystal Polymer Brushes and their Application as Alignment Layers in Liquid Crystal Cells Polymer brushes with liquid crystalline (LC) side chains were synthesized on planar glass substrates and their nematic textures were investigated. The LC polymers consist of an acrylate or a methacrylate main chain and a phenyl benzoate group as the mesogenic unit which is connected to the main chain via a flexible alkyl spacer composed of six CH2 units. The preparation of the LC polymer brushes was carried out according to the “grafting from” technique: polymerization is carried out from azo-initiators that have been previously self-assembled on the substrate. LC polymer brushes with a thickness from a few nm to 230 nm were synthesized by varying the monomer concentration and the polymerization time. The LC polymer brushes were thick enough to allow for direct observation of the nematic textures with a polarizing microscope. The LC polymer brushes grown on untreated glass substrates exhibited irregular textures (“polydomains”). The domain size is in the range of some micrometers and depends only weakly on the brush thickness. The investigations on the texture-temperature relationship of the LC brushes revealed that the brushes exhibit a surface memory effect, that is, the identical texture reappears after the LC brush sample has experienced a thermal isotropization or a solvent treatment, at which the nematic LC state has been completely destroyed. The surface memory effect is attributed to a strong anchoring of the orientation of the mesogenic units to heterogeneities at the substrate surface. The exact nature of the surface heterogeneities is unknown. The effect was observed for the LC brushes swollen with low molecular weight nematic molecules, as well. Rubbing the glass substrate with a piece of velvet cloth prior to the surface modification with the initiator and the brush growth gives rise to the formation of homogenous alignment of the mesogenic units in the LC polymer side chains. Monodomain textures were obtained for these LC brushes. The mechanism for the homogeneous alignment is based on the transfer of Nylon fibers during the rubbing process. A surfactant was mixed with the azo-initiator in modifying rubbed substrates for subsequent brush generation. Such brushes exhibited biaxial optical properties. Hybrid LC cells made from a substrate modified with biaxial brushes and a rubbed glass substrate show an orientation with a tilt angle of a = –15.6 . This work shows that LC brushes grown on rubbed surfaces fulfill the important criteria for alignment layers: the formation of macroscopic monodomains. First results indicate that by diluting the brush with molecules which are also covalently bound to the surface but induce a different orientation, a system is obtained in which the two conflicting alignment mechanisms can be used to generate a tilted alignment. In order to allow for an application of the alignment layers into a potential product, subsequent work should focus on the questions how easy and in which range the tilt angle can be controlled.

Frame-driven Extraction of Linked Data and Ontologies from Text

Ontology design and population -core aspects of semantic technologies- re- cently have become fields of great interest due to the increasing need of domain-specific knowledge bases that can boost the use of Semantic Web. For building such knowledge resources, the state of the art tools for ontology design require a lot of human work. Producing meaningful schemas and populating them with domain-specific data is in fact a very difficult and time-consuming task. Even more if the task consists in modelling knowledge at a web scale. The primary aim of this work is to investigate a novel and flexible method- ology for automatically learning ontology from textual data, lightening the human workload required for conceptualizing domain-specific knowledge and populating an extracted schema with real data, speeding up the whole ontology production process. Here computational linguistics plays a fundamental role, from automati- cally identifying facts from natural language and extracting frame of relations among recognized entities, to producing linked data with which extending existing knowledge bases or creating new ones. In the state of the art, automatic ontology learning systems are mainly based on plain-pipelined linguistics classifiers performing tasks such as Named Entity recognition, Entity resolution, Taxonomy and Relation extraction [11]. These approaches present some weaknesses, specially in capturing struc- tures through which the meaning of complex concepts is expressed [24]. Humans, in fact, tend to organize knowledge in well-defined patterns, which include participant entities and meaningful relations linking entities with each other. In literature, these structures have been called Semantic Frames by Fill- 6 Introduction more [20], or more recently as Knowledge Patterns [23]. Some NLP studies has recently shown the possibility of performing more accurate deep parsing with the ability of logically understanding the structure of discourse [7]. In this work, some of these technologies have been investigated and em- ployed to produce accurate ontology schemas. The long-term goal is to collect large amounts of semantically structured information from the web of crowds, through an automated process, in order to identify and investigate the cognitive patterns used by human to organize their knowledge.