A New Approach for Processing Natural-Language Queries to Semantic Web Triplestores

As the main train service provider company in Indonesia, PT Kereta Api Indonesia (PT KAI) has many customers who need information. In order to maintain customer loyalty, PT KAI must respond quickly and be adaptive to technology to provide the best service to customers. Limited human resources make PT KAI unable to serve customers simultaneously, so customers often have to wait for a response. In order to provide the best service, automatic messages are needed in order to help customer service performance respond quickly and at the same time with no cost, access anytime and anywhere. This study proposes a new approach with chatbots as a medium for conveying automatic information quickly and simultaneously. This chatbot is made with a computational language that focuses on natural language modeling and cosine similarity as a method for calculating the proximity of inputs and databases. This research can help PT KAI's customer service workers to answer customer needs automatically.

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A New Approach to Creation of an Artificial Intellect and Method of its Implementation

Journal of Artificial General Intelligence ◽

10.2478/jagi-2021-0004 ◽

2021 ◽

Vol 12 (1) ◽

pp. 87-110

Author(s):

Wladimir Stalski

Keyword(s):

Natural Language ◽

Work Experience ◽

Humanoid Robot ◽

Life Experience ◽

Private Life ◽

Personal Life ◽

Human Model ◽

Self Awareness ◽

New Approach ◽

Population Education

Abstract On the basis of the author’s earlier works, the article proposes a new approach to creating an artificial intellect system in a model of a human being that is presented as the unification of an intellectual agent and a humanoid robot (ARb). In accordance with the proposed new approach, the development of an artificial intellect is achieved by teaching a natural language to an ARb, and by its utilization for communication with ARbs and humans, as well as for reflections. A method is proposed for the implementation of the approach. Within the framework of that method, a human model is “brought up” like a child, in a collective of automatons and children, whereupon an ARb must master a natural language and reflection, and possess self-awareness. Agent robots (ARbs) propagate and their population evolves; that is ARbs develop cognitively from generation to generation. ARbs must perform the tasks they were given, such as computing, whereupon they are then assigned time for “private life” for improving their education as well as for searching for partners for propagation. After having received an education, every agent robot may be viewed as a “person” who is capable of activities that contain elements of creativity. The development of ARbs thanks to the evolution of their population, education, and personal “life” experience, including “work” experience, which is mastered in a collective of humans and automatons.

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Processing Natural Language Queries in Semantic Web Applications

10.11159/cist21.108 ◽

2021 ◽

Author(s):

Neli Zlatareva ◽

Devansh Amin

Keyword(s):

Semantic Web ◽

Natural Language ◽

Web Applications

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From Natural Language to RDF Graphs with Pregroups

10.31219/osf.io/xe28z ◽

2017 ◽

Author(s):

Antonin Delpeuch ◽

Anne Preller

Keyword(s):

Side Effects ◽

Semantic Web ◽

Natural Language ◽

Relative Clauses ◽

Semantic Category ◽

Target Language ◽

Pregroup Grammars ◽

Unbounded Dependencies ◽

Efficient Type ◽

Rdf Graphs

We define an algorithm translating natural language sentences to the formal syntax of RDF, an existential conjunctive logic widely used on the Semantic Web. Our translationis based on pregroup grammars, an efficient type-logical grammatical framework with atransparent syntax-semantics interface. We introduce a restricted notion of side effects inthe semantic category of finitely generated free semimodules over {0,1} to that end.The translation gives an intensional counterpart to previous extensional models.We establish a one-to-one correspondence between extensional models and RDF models such that satisfaction is preserved. Our translation encompasses the expressivity of the target language and supports complex linguistic constructions like relative clauses and unbounded dependencies.

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Geocoding Tweets Based on Semantic Web and Ontologies

Innovations, Developments, and Applications of Semantic Web and Information Systems - Advances in Web Technologies and Engineering ◽

10.4018/978-1-5225-5042-6.ch014 ◽

2018 ◽

pp. 372-392

Author(s):

Imelda Escamilla ◽

Miguel Torres Ruíz ◽

Marco Moreno Ibarra ◽

Vladimir Luna Soto ◽

Rolando Quintero ◽

...

Keyword(s):

Semantic Web ◽

Natural Language ◽

Mexico City ◽

Spatial Relationships ◽

Spatial Analyses ◽

Human Ability ◽

Share Information

Human ability to understand approximate references to locations, disambiguated by means of context and reasoning about spatial relationships, is the key to describe spatial environments and to share information about them. In this paper, we propose an approach for geocoding that takes advantage of the spatial relationships contained in the text of tweets, using semantic web, ontologies and spatial analyses. Microblog text has special characteristics (e.g. slang, abbreviations, acronyms, etc.) and thus represents a special variation of natural language. The main objective of this work is to associate spatial relationships found in text with a spatial footprint, to determine the location of the event described in the tweet. The feasibility of the proposal is demonstrated using a corpus of 200,000 tweets posted in Spanish related with traffic events in Mexico City.

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