Auflistung nach:
Auflistung Künstliche Intelligenz 35(3-4) - Oktober 2021 nach Titel
1 - 10 von 20
Treffer pro Seite
Sortieroptionen
- ZeitschriftenartikelArtificial Intelligence: Mind, Computer and the Dance of the Wu Li Masters(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Siekmann, JörgIn these days of exuberant fantasies about the future development of artificial intelligence—mostly written by people who have never in their lives developed an AI program—the GFFT (Society for the Promotion of Technology Transfer) has also unleashed a competition on future AI scenarios to honour Wolfgang Bibel. Because I was allowed to give the laudatory speech for Wolfgang, I was also asked to contribute something to the pen. And because, despite everything else, it is not reprehensible to think about the future, I could not refrain from doing so. Here is my somewhat expanded contribution.
- ZeitschriftenartikelClimbing the Hill of Computational Semantics(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Hershcovich, Daniel; Donatelli, Lucia
- ZeitschriftenartikelConsciousness: Just Another Technique?(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Barthelmeß, Ulrike; Furbach, UlrichThis note is intended as a contribution to the discussion whether artificial systems can have consciousness. Based on the notion of Tononi’s Information Integration Theory we will argue, that AI systems that have to reason with large knowledge bases need such techniques in order to handle them efficiently. We furthermore discuss mind-wandering and creativity on this basis.
- ZeitschriftenartikelCorrection to: Just-In-Time Constraint-Based Inference for Qualitative Spatial and Temporal Reasoning(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Sioutis, Michael
- ZeitschriftenartikelData, Knowledge, and Computation(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Igel, Christian
- ZeitschriftenartikelDesigning a Uniform Meaning Representation for Natural Language Processing(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Van Gysel, Jens E. L.; Vigus, Meagan; Chun, Jayeol; Lai, Kenneth; Moeller, Sarah; Yao, Jiarui; O’Gorman, Tim; Cowell, Andrew; Croft, William; Huang, Chu-Ren; Hajič, Jan; Martin, James H.; Oepen, Stephan; Palmer, Martha; Pustejovsky, James; Vallejos, Rosa; Xue, NianwenIn this paper we present Uniform Meaning Representation (UMR), a meaning representation designed to annotate the semantic content of a text. UMR is primarily based on Abstract Meaning Representation (AMR), an annotation framework initially designed for English, but also draws from other meaning representations. UMR extends AMR to other languages, particularly morphologically complex, low-resource languages. UMR also adds features to AMR that are critical to semantic interpretation and enhances AMR by proposing a companion document-level representation that captures linguistic phenomena such as coreference as well as temporal and modal dependencies that potentially go beyond sentence boundaries.
- ZeitschriftenartikelDissertation Abstract: The Syntax, Semantics and Pragmatics of Japanese Addressee-Honorific Markers(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Yamada, AkitakaThis dissertation is a case study of filling the gap between the two disciplines about human inference systems: theoretical linguistics and statistics. The main linguistic instance examined in this study is honorificity, in particular honorificity encoded by the Japanese addressee-honorific marker (AHM) -mas . Its linguistic properties and its effect on our inference are given a systematic explanation, in such a way that the traditions of statistics and theoretical linguistics are both maximally respected. For the morphosyntax, -mas is distributed in an unexpected position. It is proposed that this is due to an agreement. For the inference, the dynamicity is modeled as a Bayesian update, and the trigger of the update is the denotation amenable to the proposal of the previous linguistic literature.
- ZeitschriftenartikelDissertation Abstract:Learning High Precision Lexical Inferences(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Shwartz, VeredThe fundamental goal of natural language processing is to build models capable of human-level understanding of natural language. One of the obstacles to building such models is lexical variability , i.e. the ability to express the same meaning in various ways. Existing text representations excel at capturing relatedness (e.g. blue / red ), but they lack the fine-grained distinction of the specific semantic relation between a pair of words. This article is a summary of a Ph.D. dissertation submitted to Bar-Ilan University in 2019, under the supervision of Professor Ido Dagan of the Computer Science Department. The dissertation explored methods for recognizing and extracting semantic relationships between concepts ( cat is a type of animal ), the constituents of noun compounds (baby oil is oil for babies), and verbal phrases (‘X died at Y’ means the same as ‘X lived until Y’ in certain contexts). The proposed models outperform highly competitive baselines and improve the state-of-the-art in several benchmarks. The dissertation concludes in discussing two challenges in the way of human-level language understanding: developing more accurate text representations and learning to read between the lines.
- ZeitschriftenartikelDo It Yourself, but Not Alone: Companion-Technology for Home Improvement—Bringing a Planning-Based Interactive DIY Assistant to Life(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Bercher, Pascal; Behnke, Gregor; Kraus, Matthias; Schiller, Marvin; Manstetten, Dietrich; Dambier, Michael; Dorna, Michael; Minker, Wolfgang; Glimm, Birte; Biundo, SusanneWe report on the technology transfer project “Do it yourself, but not alone: Companion -Technology for Home Improvement” that was carried out by Ulm University in cooperation with Robert Bosch GmbH. We developed a prototypical assistance system that assists a Do It Yourself (DIY) handyman in carrying out DIY projects. The assistant, based on various AI and dialog management capabilities, generates a sequence of detailed instructions that users may just follow or adapt according to their individual preferences. It features explanation capabilities as well as pro-active support based on communication with the user as well as with the involved tools. We report on the project’s main achievements, including the findings of various empirical studies conducted in various development stages of the prototype.
- ZeitschriftenartikelDraw mir a Sheep: A Supersense-based Analysis of German Case and Adposition Semantics(KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Prange, Jakob; Schneider, NathanAdpositions and case markers are ubiquitous in natural language and express a wide range of meaning relations that can be of crucial relevance for many NLP and AI tasks. However, capturing their semantics in a comprehensive yet concise, as well as cross-linguistically applicable way has remained a challenge over the years. To address this, we adapt the largely language-agnostic SNACS framework to German, defining language-specific criteria for identifying adpositional expressions and piloting a supersense-annotated German corpus. We compare our approach with prior work on both German and multilingual adposition semantics, and discuss our empirical findings in the context of potential applications.