Computer Science and Metaphysics: A Cross-Fertilization

Computational philosophy is the use of mechanized computational techniques to unearth philosophical insights that are either difficult or impossible to find using traditional philosophical methods. Computational metaphysics is computational philosophy with a focus on metaphysics. In this paper, we (a) develop results in modal metaphysics whose discovery was computer assisted, and (b) conclude that these results work not only to the obvious benefit of philosophy but also, less obviously, to the benefit of computer science, since the new computational techniques that led to these results may be more broadly applicable within computer science. The paper includes a description of our background methodology and how it evolved, and a discussion of our new results.Comment: 39 pages, 3 figure

Linked data enrichment with self-unfolding URIs

Linked Data resources are identified by Uniform Resource Identifiers. It is an important step in any Linked Data project to define the conventions for URI assignments. In some cases resources already have their natural identifiers, or they can be inherited from previous databases. However, there are cases when frequent insertions of triple sets occur without any convenient way for identification and grouping of them. In this paper we elaborate on a mechanism that makes handling complex and frequent insertions easier, and also provides the benefits of simple authoring together with rich querying and reasoning on the data. We show how to eliminate some of the time consuming and error prone aspects of Linked Data authoring by introducing the self-unfolding URI concept. This solution generates RDF description to entities based on information encoded in their URIs. For the generation of these new RDF triples we propose templates that can be implemented by SPARQL Insert queries

Retrieval interference and semantic interpretation

Similarity-based interference has played an important role in motivating cue-based models of memory retrieval during language comprehension. One example of interference comes from illusions of grammaticality, where ungrammatical sentences are perceived as grammatical (e.g. ‘the key to the cabinets were rusty’). While such effects indicate interference influences perception of sentence grammaticality, less is known about how interference influences the semantic interpretation assigned to a sentence. We report two reading experiments that manipulated sentence plausibility, rather than grammaticality, as a diagnostic of interference. In both experiments, although reading times were longer for implausible sentences, this plausibility effect was reliably attenuated when a distractor item partially matched the cues at retrieval. We interpret these results as being compatible with the predictions of cue-based parsing. The illusions of plausibility that we report indicate that similarity-based retrieval interference has a potent influence on the semantic interpretation that is assigned to a sentence during processing

Okos egyetemi szolgáltatásokat megalapozó kapcsolt adathalmazok

Az egyetemi kampuszokon megforduló emberek információs igénye jelentős átfedést mutat. Ezért nagyon fontos létrehozni egy közös adatmodellt, ami lehetővé teszi a különböző heterogén forrásokból származó adatok összekapcsolását és ezáltal a felmerülő információs igények emelt szintű kiszolgálását az összekapcsolt adatokon alapuló új alkalmazások révén. A disszertáció azt a kérdést vizsgálja, hogy a megfelelő gépi feldolgozásra alkalmas információ megosztásával hogyan tudnak a 21. században az egyetemek lépést tartani az új igényekkel, egyfajta “okos egyetemként” működve. Elsőként részletezi az OLOUD ontológiát, amely egy egyetem oktatási tevékenységével kapcsolatos szervezetek, kurzusok, képzések, személyek, diplomák stb. leírására használható. Az OLOUD ontológia integrál több használatban lévő ontológiát kiegészítve a magyar egyetemekre vonatkozó specializációkkal. Második témaként a dolgozat az egyetemi kampuszon belüli navigáció szemantikus web alapú megközelítését vizsgálja. Ehhez először az épületek helyiségeinek elhelyezkedését, viszonyát leíró iLOC ontológiát definiálja. Az épületen belül különböző helyszínek (POI-k), illetve a köztük található közvetlen útvonalak adhatók meg. Ezután a disszertáció a beltéri navigáció kérdéseivel foglalkozik: ha az adatokat ilyen módon szemantikus formában tároljuk, akkor a komplex útvonalak előállíthatóak gráf lekérdező nyelvek, például SPARQL, segítségével. A dolgozat példa lekérdezéseken keresztül mutatja be, hogy az így előálló OLOUD és iLOC ontológiák új felhasználási esetekre adnak lehetőséget, akár a felsőoktatási kereteken túlmutatva, támogatva a navigációt kórházakban, múzeumokban, repülőtereken és más nyilvános helyeken. A komplex felhasználási esetek kezeléséhez szükséges volt bevezetni a kibontható URI-k fogalmát is.On a university campus it has great importance to establish a common data model which enables the interconnection of fragmented data from heterogeneous data sources. This thesis contributes to the “Smart Campus” topic, researching the opportunities and benefits of publishing university related open linked data in a machine consumable way. First, it details the OLOUD Ontology, which can be used to describe concepts related to university education, e.g. organisation, course, subject, people, degree, etc. The OLOUD Ontology integrates multiple existing ontologies, extending them with the Hungarian specialities. Second, the thesis discusses the navigation within a university campus based on Semantic Web technologies. For this, it defines the iLOC ontology, which provides concepts to describe buildings and their inner parts. Within a building one can define locations (POIs) and direct routes between them. Then the thesis focuses on indoor navigation: if the data is stored in such a way in a semantic format, then the complex routes can be calculated using graph query languages, like SPARQL. With example queries it has been demonstrated that the OLOUD and iLOC ontologies are enabling new use cases, even beyond the scope of the higher education, supporting navigation in hospitals, museums, airports and other public places. To support the complex use cases it was necessary to introduce the new method of Self-Unfolding URIs too

Beyond associations:Sensitivity to structure in pre-schoolers' linguistic predictions

One influential view of language acquisition is that children master structural generalizations by making and learning from structure-informed predictions. Previous work has shown that from 3 years of age children can use semantic associations to generate predictions. However, it is unknown whether they can generate predictions by combining these associations with knowledge of linguistic structure. We recorded the eye movements of pre-schoolers while they listened to sentences such as Pingu will ride the horse. Upon hearing ride, children predictively looked at a horse (a strongly associated and plausible patient of ride), and mostly ignored a cowboy (equally strongly associated, but an implausible patient). In a separate experiment, children did not rapidly look at the horse when they heard You can show Pingu … “riding”, showing that they do not quickly activate strongly associated patients when there are no structural constraints. Our findings demonstrate that young children’s predictions are sensitive to structure, providing support for predictive-learning models of language acquisition