2,920 research outputs found
Advanced Knowledge Technologies at the Midterm: Tools and Methods for the Semantic Web
The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the authorâs and shouldnât be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In a celebrated essay on the new electronic media, Marshall McLuhan wrote in 1962:Our private senses are not closed systems but are endlessly translated into each other in that experience which we call consciousness. Our extended senses, tools, technologies, through the ages, have been closed systems incapable of interplay or collective awareness. Now, in the electric age, the very
instantaneous nature of co-existence among our technological instruments has created a crisis quite new in human history. Our extended faculties and senses now constitute a single field of experience which demands that they become collectively conscious. Our technologies, like our private senses, now demand an interplay and ratio that makes rational co-existence possible. As long as our technologies were as slow as the wheel or the alphabet or money, the fact that
they were separate, closed systems was socially and psychically supportable. This is not true now when sight and sound and movement are simultaneous and global in extent. (McLuhan 1962, p.5, emphasis in original)Over forty years later, the seamless interplay that McLuhan demanded between our
technologies is still barely visible. McLuhanâs predictions of the spread, and increased importance, of electronic media have of course been borne out, and the worlds of business, science and knowledge storage and transfer have been revolutionised. Yet
the integration of electronic systems as open systems remains in its infancy.Advanced Knowledge Technologies (AKT) aims to address this problem, to create a view of knowledge and its management across its lifecycle, to research and create the
services and technologies that such unification will require. Half way through its sixyear span, the results are beginning to come through, and this paper will explore some of the services, technologies and methodologies that have been developed. We hope to give a sense in this paper of the potential for the next three years, to discuss the insights and lessons learnt in the first phase of the project, to articulate the challenges and issues that remain.The WWW provided the original context that made the AKT approach to knowledge
management (KM) possible. AKT was initially proposed in 1999, it brought together an interdisciplinary consortium with the technological breadth and complementarity to create the conditions for a unified approach to knowledge across its lifecycle. The
combination of this expertise, and the time and space afforded the consortium by the
IRC structure, suggested the opportunity for a concerted effort to develop an approach
to advanced knowledge technologies, based on the WWW as a basic infrastructure.The technological context of AKT altered for the better in the short period between the development of the proposal and the beginning of the project itself with the development of the semantic web (SW), which foresaw much more intelligent manipulation and querying of knowledge. The opportunities that the SW provided for e.g., more intelligent retrieval, put AKT in the centre of information technology innovation and knowledge management services; the AKT skill set would clearly be central for the exploitation of those opportunities.The SW, as an extension of the WWW, provides an interesting set of constraints to
the knowledge management services AKT tries to provide. As a medium for the
semantically-informed coordination of information, it has suggested a number of ways in which the objectives of AKT can be achieved, most obviously through the
provision of knowledge management services delivered over the web as opposed to the creation and provision of technologies to manage knowledge.AKT is working on the assumption that many web services will be developed and provided for users. The KM problem in the near future will be one of deciding which services are needed and of coordinating them. Many of these services will be largely or entirely legacies of the WWW, and so the capabilities of the services will vary. As well as providing useful KM services in their own right, AKT will be aiming to exploit this opportunity, by reasoning over services, brokering between them, and providing essential meta-services for SW knowledge service management.Ontologies will be a crucial tool for the SW. The AKT consortium brings a lot of expertise on ontologies together, and ontologies were always going to be a key part of the strategy. All kinds of knowledge sharing and transfer activities will be mediated by ontologies, and ontology management will be an important enabling task. Different
applications will need to cope with inconsistent ontologies, or with the problems that will follow the automatic creation of ontologies (e.g. merging of pre-existing
ontologies to create a third). Ontology mapping, and the elimination of conflicts of
reference, will be important tasks. All of these issues are discussed along with our
proposed technologies.Similarly, specifications of tasks will be used for the deployment of knowledge services over the SW, but in general it cannot be expected that in the medium term there will be standards for task (or service) specifications. The brokering metaservices
that are envisaged will have to deal with this heterogeneity.The emerging picture of the SW is one of great opportunity but it will not be a wellordered, certain or consistent environment. It will comprise many repositories of legacy data, outdated and inconsistent stores, and requirements for common understandings across divergent formalisms. There is clearly a role for standards to play to bring much of this context together; AKT is playing a significant role in these efforts. But standards take time to emerge, they take political power to enforce, and they have been known to stifle innovation (in the short term). AKT is keen to understand the balance between principled inference and statistical processing of web content. Logical inference on the Web is tough. Complex queries using traditional AI inference methods bring most distributed computer systems to their knees. Do we set up semantically well-behaved areas of the Web? Is any part of the Web in which
semantic hygiene prevails interesting enough to reason in? These and many other
questions need to be addressed if we are to provide effective knowledge technologies
for our content on the web
TDL : a type description language for HPSG. - Part 1: Overview
Unification-based grammar formalisms have become the predominant paradigm in natural language processing NLP and computational linguistics CL. Their success stems from the fact that they can be seen as high-level declarative programming languages for linguists, which allow them to express linguistic knowledge in a monotonic fashion. More over, such formalisms can be given a precise set theoretical semantics. This paper presents mathcal{TDL}, a typed featurebased language and inference system, which is specically designed to support highly lexicalized grammar theories like HPSG, FUG, or CUG. mathcal{TDL} allows the user to define possibly recursive hierarchically ordered types consisting of type constraints and feature constraints over the boolean connectives wedge, vee, and neg. mathcal{TDL} distinguishes between avm types (open-world reasoning), sort types (closed-world reasoning), built-in types and atoms, and allows the declaration of partitions and incompatible types. Working with partially as well as with fully expanded types is possible, both at definition time and at run time. mathcal{TDL} is incremental, i.e., it allows the redefinition of types and the use of undefined types. Efficient reasoning is accomplished through four specialized reasoners
Developmental Bootstrapping of AIs
Although some current AIs surpass human abilities in closed artificial worlds
such as board games, their abilities in the real world are limited. They make
strange mistakes and do not notice them. They cannot be instructed easily, fail
to use common sense, and lack curiosity. They do not make good collaborators.
Mainstream approaches for creating AIs are the traditional manually-constructed
symbolic AI approach and generative and deep learning AI approaches including
large language models (LLMs). These systems are not well suited for creating
robust and trustworthy AIs. Although it is outside of the mainstream, the
developmental bootstrapping approach has more potential. In developmental
bootstrapping, AIs develop competences like human children do. They start with
innate competences. They interact with the environment and learn from their
interactions. They incrementally extend their innate competences with
self-developed competences. They interact and learn from people and establish
perceptual, cognitive, and common grounding. They acquire the competences they
need through bootstrapping. However, developmental robotics has not yet
produced AIs with robust adult-level competences. Projects have typically
stopped at the Toddler Barrier corresponding to human infant development at
about two years of age, before their speech is fluent. They also do not bridge
the Reading Barrier, to skillfully and skeptically draw on the socially
developed information resources that power current LLMs. The next competences
in human cognitive development involve intrinsic motivation, imitation
learning, imagination, coordination, and communication. This position paper
lays out the logic, prospects, gaps, and challenges for extending the practice
of developmental bootstrapping to acquire further competences and create
robust, resilient, and human-compatible AIs.Comment: 102 pages, 29 figure
Fourth Conference on Artificial Intelligence for Space Applications
Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming
An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications
Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered
Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design
The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface
Parsing and Evaluation. Improving Dependency Grammars Accuracy. Anà lisi Sintà ctica Automà tica i Avaluació. Millora de qualitat per a Gramà tiques de Dependències
Because parsers are still limited in analysing specific ambiguous constructions, the research presented in this thesis mainly aims to contribute to the improvement of parsing performance when it has knowledge integrated in order to deal with ambiguous linguistic phenomena. More precisely, this thesis intends to provide empirical solutions to the disambiguation of prepositional phrase attachment and argument recognition in order to assist parsers in generating a more accurate syntactic analysis. The disambiguation of these two highly ambiguous linguistic phenomena by the integration of knowledge about the language necessarily relies on linguistic and statistical strategies for knowledge acquisition.
The starting point of this research proposal is the development of a rule-based grammar for Spanish and for Catalan following the theoretical basis of Dependency Grammar (Tesnière, 1959; MelâÄuk, 1988) in order to carry out two experiments about the integration of automatically- acquired knowledge. In order to build two robust grammars that understand a sentence, the FreeLing pipeline (PadrĂł et al., 2010) has been used as a framework. On the other hand, an eclectic repertoire of criteria about the nature of syntactic heads is proposed by reviewing the postulates of Generative Grammar (Chomsky, 1981; Bonet and SolĂ , 1986; Haegeman, 1991) and Dependency Grammar (Tesnière, 1959; MelâÄuk, 1988). Furthermore, a set of dependency relations is provided and mapped to Universal Dependencies (Mcdonald et al., 2013).
Furthermore, an empirical evaluation method has been designed in order to carry out both a quantitative and a qualitative analysis. In particular, the dependency parsed trees generated by the grammars are compared to real linguistic data. The quantitative evaluation is based on the Spanish Tibidabo Treebank (Marimon et al., 2014), which is large enough to carry out a real analysis of the grammars performance and which has been annotated with the same formalism as the grammars, syntactic dependencies. Since the criteria between both resources are differ- ent, a process of harmonization has been applied developing a set of rules that automatically adapt the criteria of the corpus to the grammar criteria. With regard to qualitative evaluation, there are no available resources to evaluate Spanish and Catalan dependency grammars quali- tatively. For this reason, a test suite of syntactic phenomena about structure and word order has been built. In order to create a representative repertoire of the languages observed, descriptive grammars (Bosque and Demonte, 1999; SolĂ et al., 2002) and the SenSem Corpus (VĂĄzquez and FernĂĄndez-Montraveta, 2015) have been used for capturing relevant structures and word order patterns, respectively.
Thanks to these two tools, two experiments have been carried out in order to prove that knowl- edge integration improves the parsing accuracy. On the one hand, the automatic learning of lan- guage models has been explored by means of statistical methods in order to disambiguate PP- attachment. More precisely, a model has been learned with a supervised classifier using Weka (Witten and Frank, 2005). Furthermore, an unsupervised model based on word embeddings has been applied (Mikolov et al., 2013a,b). The results of the experiment show that the supervised method is limited in predicting solutions for unseen data, which is resolved by the unsupervised method since provides a solution for any case. However, the unsupervised method is limited if it
Parsing and Evaluation Improving Dependency Grammars Accuracy
only learns from lexical data. For this reason, training data needs to be enriched with the lexical value of the preposition, as well as semantic and syntactic features. In addition, the number of patterns used to learn language models has to be extended in order to have an impact on the grammars.
On the other hand, another experiment is carried out in order to improve the argument recog- nition in the grammars by the acquisition of linguistic knowledge. In this experiment, knowledge is acquired automatically from the extraction of verb subcategorization frames from the SenSem Corpus (VĂĄzquez and FernĂĄndez-Montraveta, 2015) which contains the verb predicate and its arguments annotated syntactically. As a result of the information extracted, subcategorization frames have been classified into subcategorization classes regarding the patterns observed in the corpus. The results of the subcategorization classes integration in the grammars prove that this information increases the accuracy of the argument recognition in the grammars.
The results of the research of this thesis show that grammarsâ rules on their own are not ex- pressive enough to resolve complex ambiguities. However, the integration of knowledge about these ambiguities in the grammars may be decisive in the disambiguation. On the one hand, sta- tistical knowledge about PP-attachment can improve the grammars accuracy, but syntactic and semantic information, and new patterns of PP-attachment need to be included in the language models in order to contribute to disambiguate this phenomenon. On the other hand, linguistic knowledge about verb subcategorization acquired from annotated linguistic resources show a positive influence positively on grammarsâ accuracy.Aquesta tesi vol tractar les limitacions amb què es troben els analitzadors sintĂ ctics automĂ tics actualment. Tot i els progressos que sâhan fet en lâĂ rea del Processament del Llenguatge Nat- ural en els darrers anys, les tecnologies del llenguatge i, en particular, els analitzadors sintĂ c- tics automĂ tics no han pogut traspassar el llindar de certes ambiguĂŻtats estructurals com ara lâagrupaciĂł del sintagma preposicional i el reconeixement dâarguments. Ăs per aquest motiu que la recerca duta a terme en aquesta tesi tĂŠ com a objectiu aportar millores signiflcatives de quali- tat a lâanĂ lisi sintĂ ctica automĂ tica per mitjĂ de la integraciĂł de coneixement lingĂźĂstic i estadĂstic per desambiguar construccions sintĂ ctiques ambigĂźes.
El punt de partida de la recerca ha estat el desenvolupament de dâuna gramĂ tica en espanyol i una altra en catalĂ basades en regles que segueixen els postulats de la GramĂ tica de Dependèn- dencies (Tesnière, 1959; MelâÄuk, 1988) per tal de dur a terme els experiments sobre lâadquisiciĂł de coneixement automĂ tic. Per tal de crear dues gramĂ tiques robustes que analitzin i entenguin lâoraciĂł en profunditat, ens hem basat en lâarquitectura de FreeLing (PadrĂł et al., 2010), una lli- breria de Processament de Llenguatge Natural que proveeix una anĂ lisi lingĂźĂstica automĂ tica de lâoraciĂł. Per una altra banda, sâha elaborat una proposta eclèctica de criteris lingĂźĂstics per determinar la formaciĂł dels sintagmes i les clĂ usules a la gramĂ tica per mitjĂ de la revisiĂł de les propostes teòriques de la GramĂ tica Generativa (Chomsky, 1981; Bonet and SolĂ , 1986; Haege- man, 1991) i de la GramĂ tica de Dependències (Tesnière, 1959; MelâÄuk, 1988). Aquesta proposta sâacompanya dâun llistat de les etiquetes de relaciĂł de dependència que fan servir les regles de les gramĂ tques. A mĂŠs a mĂŠs de lâelaboraciĂł dâaquest llistat, sâhan establert les correspondències amb lâestĂ ndard dâanotaciĂł de les Dependències Universals (Mcdonald et al., 2013).
Alhora, sâha dissenyat un sistema dâavaluaciĂł empĂric que tĂŠ en compte lâanĂ lisi quantitativa i qualitativa per tal de fer una valoraciĂł completa dels resultats dels experiments. Precisament, es tracta una tasca empĂrica pel fet que es comparen les anĂ lisis generades per les gramĂ tiques amb dades reals de la llengua. Per tal de dur a terme lâavaluaciĂł des dâuna perspectiva quan- titativa, sâha fet servir el corpus Tibidabo en espanyol (Marimon et al., 2014) disponible nomĂŠs en espanyol que ĂŠs prou extens per construir una anĂ lisi real de les gramĂ tiques i que ha estat anotat amb el mateix formalisme que les gramĂ tiques. En concret, per tal com els criteris de les gramĂ tiques i del corpus no sĂłn coincidents, sâha dut a terme un procĂŠs dâharmonitzaciĂł de cri- teris per mitjĂ dâunes regles creades manualment que adapten automĂ ticament lâestructura i la relaciĂł de dependència del corpus al criteri de les gramĂ tiques. Pel que fa a lâavaluaciĂł qualitativa, pel fet que no hi ha recursos disponibles en espanyol i catalĂ , hem dissenyat un reprertori de test de fenòmens sintĂ ctics estructurals i relacionats amb lâordre de lâoraciĂł. Amb lâobjectiu de crear un repertori representatiu de les llengĂźes estudiades, sâhan fet servir gramĂ tiques descriptives per fornir el repertori dâestructures sintĂ ctiques (Bosque and Demonte, 1999; SolĂ et al., 2002) i el Corpus SenSem (VĂĄzquez and FernĂĄndez-Montraveta, 2015) per capturar automĂ ticament lâordre oracional.
GrĂ cies a aquestes dues eines, sâhan pogut dur a terme dos experiments per provar que la integraciĂł de coneixement en lâanĂ lisi sintĂ ctica automĂ tica en millora la qualitat. Dâuna banda,
Parsing and Evaluation Improving Dependency Grammars Accuracy
sâha explorat lâaprenentatge de models de llenguatge per mitjĂ de models estadĂstics per tal de proposar solucions a lâagrupaciĂł del sintagma preposicional. MĂŠs concretament, sâha desen- volupat un model de llenguatge per mitjĂ dâun classiflcador dâaprenentatge supervisat de Weka (Witten and Frank, 2005). A mĂŠs a mĂŠs, sâha après un model de llenguatge per mitjĂ dâun mètode no supervisat basat en lâaproximaciĂł distribucional anomenat word embeddings (Mikolov et al., 2013a,b). Els resultats de lâexperiment posen de manifest que el mètode supervisat tĂŠ greus lim- itacions per fer donar una resposta en dades que no ha vist prèviament, cosa que ĂŠs superada pel mètode no supervisat pel fet que ĂŠs capaç de classiflcar qualsevol cas. De tota manera, el mètode no supervisat que sâha estudiat ĂŠs limitat si aprèn a partir de dades lèxiques. Per aquesta raĂł, ĂŠs necessari que les dades utilitzades per entrenar el model continguin el valor de la preposi- ciĂł, trets sintĂ ctics i semĂ ntics. A mĂŠs a mĂŠs, cal ampliar el nĂşmero de patrons apresos per tal dâampliar la cobertura dels models i tenir un impacte en els resultats de les gramĂ tiques.
Dâuna altra banda, sâha proposat una manera de millorar el reconeixement dâarguments a les gramĂ tiques per mitjĂ de lâadquisiciĂł de coneixement lingĂźĂstic. En aquest experiment, sâha op- tat per extreure automĂ ticament el coneixement en forma de classes de subcategoritzaciĂł verbal dâel Corpus SenSem (VĂĄzquez and FernĂĄndez-Montraveta, 2015), que contĂŠ anotats sintĂ ctica- ment el predicat verbal i els seus arguments. A partir de la informaciĂł extreta, sâha classiflcat les diverses diĂ tesis verbals en classes de subcategoritzaciĂł verbal en funciĂł dels patrons observats en el corpus. Els resultats de la integraciĂł de les classes de subcategoritzaciĂł a les gramĂ tiques mostren que aquesta informaciĂł determina positivament el reconeixement dels arguments.
Els resultats de la recerca duta a terme en aquesta tesi doctoral posen de manifest que les regles de les gramĂ tiques no sĂłn prou expressives per elles mateixes per resoldre ambigĂźitats complexes del llenguatge. No obstant això, la integraciĂł de coneixement sobre aquestes am- bigĂźitats pot ser decisiu a lâhora de proposar una soluciĂł. Dâuna banda, el coneixement estadĂstic sobre lâagrupaciĂł del sintagma preposicional pot millorar la qualitat de les gramĂ tiques, però per aflrmar-ho cal incloure informaciĂł sintĂ ctica i semĂ ntica en els models dâaprenentatge automĂ tic i capturar mĂŠs patrons per contribuir en la desambiguaciĂł de fenòmens complexos. Dâuna al- tra banda, el coneixement lingĂźĂstic sobre subcategoritzaciĂł verbal adquirit de recursos lingĂźĂs- tics anotats influeix decisivament en la qualitat de les gramĂ tiques per a lâanĂ lisi sintĂ ctica au- tomĂ tica
An overview of decision table literature 1982-1995.
This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.
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