Extending an Indonesian Semantic Analysis-based Question Answering System with Linguistic and World Knowledge Axioms

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

Systematic Literature Review on Ontology-based Indonesian Question Answering System

Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for accurate responses. Secondly, template-based SPARQL query construction, commonly used in Indonesian QA systems, suffers from semantic gaps and inflexibility. Advanced techniques like semantic matching algorithms and dynamic template generation can bridge these gaps and adapt to evolving ontologies. Thirdly, lexical gaps and ambiguity hinder QA systems. Bridging vocabulary mismatches between user queries and ontology labels remains a challenge. Strategies like synonym expansion, word embedding, and ontology enrichment must be explored further to overcome these challenges. Lastly, the review discusses the potential of developing multi-domain ontologies to broaden the knowledge coverage of QA systems. While this presents complex linguistic and ontological challenges, it offers the advantage of responding to various user queries across various domains. This literature review identifies crucial challenges in developing ontology-based Indonesian QA systems and suggests innovative approaches to address these challenges

Parsing dan Konversi Kalimat Tanya Konfirmatif Menjadi Query Sparql Menggunakan Pendekatan Top-Down Parsing

Penelitian ini merupakan lanjutan penelitian sebelumnya (Syarief, 2014), yaitu dengan menambahkan fitur pengenalan kalimat tanya konfirmasi, yaitu kalimat tanya yang hanya membutuhkan jawaban ya atau tidak. Data yang dibahas dalam peneltian ini menggunakan ontologi OntoMotif (Syarief, 2015) sebagai ontologi utama. Pendekatan teknik parsing yang digunakan adalah top-down parsing dengan menekankan pada pengenalan predikat. Penyusunan gramatika kalimat tanya konfirmatif dalam penelitian ini difokuskan pada pengenalan kalimat berita sederhana berbentuk SPO (subjek – predikat - objek) dengan 4 macam predikat utama, yaitu diproduksi, memproduksi, mempunyai, dan dimiliki. Dari hasil pengujian, dapat disimpulkan bahwa pendekatan teknik parsing dan konversi dalam penelitian ini berhasil menjawab pertanyaan yang cukup bervariasi seputar fitur-fitur kendaraan bermotor

Ontological Approach for Semantic Modelling of Malay Translated Qur’an

This thesis contributes to the areas of ontology development and analysis, natural language processing (NLP), Information Retrieval (IR), and Language Resource and Corpus Development. Research in Natural Language Processing and semantic search for English has shown successful results for more than a decade. However, it is difficult to adapt those techniques to the Malay language, because its complex morphology and orthographic forms are very different from English. Moreover, limited resources and tools for computational linguistic analysis are available for Malay. In this thesis, we address those issues and challenges by proposing MyQOS, the Malay Qur’an Ontology System, a prototype ontology-based IR with semantics for representing and accessing a Malay translation of the Qur’an. This supports the development of a semantic search engine and a question answering system and provides a framework for storing and accessing a Malay language corpus and providing computational linguistics resources. The primary use of MyQOS in the current research is for creating and improving the quality and accuracy of the query mechanism to retrieve information embedded in the Malay text of the Qur’an translation. To demonstrate the feasibility of this approach, we describe a new architecture of morphological analysis for MyQOS and query algorithms based on MyQOS. Data analysis consisted of two measures; precision and recall, where data was obtained from MyQOS Corpus conducted in three search engines. The precision and recall for semantic search are 0.8409 (84%) and 0.8043(80%), double the results of the question-answer search which are 0.4971(50%) for precision and 0.6027 (60%) for recall. The semantic search gives high precision and high recall comparing the other two methods. This indicates that semantic search returns more relevant results than irrelevant ones. To conclude, this research is among research in the retrieval of the Qur’an texts in the Malay language that managed to outline state-of-the-art information retrieval system models. Thus, the use of MyQOS will help Malay readers to understand the Qur’an in better ways. Furthermore, the creation of a Malay language corpus and computational linguistics resources will benefit other researchers, especially in religious texts, morphological analysis, and semantic modelling

An ontology for human-like interaction systems

This report proposes and describes the development of a Ph.D. Thesis aimed at building an ontological knowledge model supporting Human-Like Interaction systems. The main function of such knowledge model in a human-like interaction system is to unify the representation of each concept, relating it to the appropriate terms, as well as to other concepts with which it shares semantic relations. When developing human-like interactive systems, the inclusion of an ontological module can be valuable for both supporting interaction between participants and enabling accurate cooperation of the diverse components of such an interaction system. On one hand, during human communication, the relation between cognition and messages relies in formalization of concepts, linked to terms (or words) in a language that will enable its utterance (at the expressive layer). Moreover, each participant has a unique conceptualization (ontology), different from other individual’s. Through interaction, is the intersection of both part’s conceptualization what enables communication. Therefore, for human-like interaction is crucial to have a strong conceptualization, backed by a vast net of terms linked to its concepts, and the ability of mapping it with any interlocutor’s ontology to support denotation. On the other hand, the diverse knowledge models comprising a human-like interaction system (situation model, user model, dialogue model, etc.) and its interface components (natural language processor, voice recognizer, gesture processor, etc.) will be continuously exchanging information during their operation. It is also required for them to share a solid base of references to concepts, providing consistency, completeness and quality to their processing. Besides, humans usually handle a certain range of similar concepts they can use when building messages. The subject of similarity has been and continues to be widely studied in the fields and literature of computer science, psychology and sociolinguistics. Good similarity measures are necessary for several techniques from these fields such as information retrieval, clustering, data-mining, sense disambiguation, ontology translation and automatic schema matching. Furthermore, the ontological component should also be able to perform certain inferential processes, such as the calculation of semantic similarity between concepts. The principal benefit gained from this procedure is the ability to substitute one concept for another based on a calculation of the similarity of the two, given specific circumstances. From the human’s perspective, the procedure enables referring to a given concept in cases where the interlocutor either does not know the term(s) initially applied to refer that concept, or does not know the concept itself. In the first case, the use of synonyms can do, while in the second one it will be necessary to refer the concept from some other similar (semantically-related) concepts...Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaSecretario: Inés María Galván León.- Secretario: José María Cavero Barca.- Vocal: Yolanda García Rui

Quod Erat Demonstrandum: From Herodotus’ ethnographic journeys to cross-cultural research

A peer-reviewed book based on presentations at the XVIII Congress of the International Association for Cross-Cultural Psychology, 2006, Isle of Spetses, Greece. (c) 2009, International Association for Cross-Cultural Psychologyhttps://scholarworks.gvsu.edu/iaccp_proceedings/1004/thumbnail.jp

Ontology Pattern-Based Data Integration

Data integration is concerned with providing a unified access to data residing at multiple sources. Such a unified access is realized by having a global schema and a set of mappings between the global schema and the local schemas of each data source, which specify how user queries at the global schema can be translated into queries at the local schemas. Data sources are typically developed and maintained independently, and thus, highly heterogeneous. This causes difficulties in integration because of the lack of interoperability in the aspect of architecture, data format, as well as syntax and semantics of the data. This dissertation represents a study on how small, self-contained ontologies, called ontology design patterns, can be employed to provide semantic interoperability in a cross-repository data integration system. The idea of this so-called ontology pattern- based data integration is that a collection of ontology design patterns can act as the global schema that still contains sufficient semantics, but is also flexible and simple enough to be used by linked data providers. On the one side, this differs from existing ontology-based solutions, which are based on large, monolithic ontologies that provide very rich semantics, but enforce too restrictive ontological choices, hence are shunned by many data providers. On the other side, this also differs from the purely linked data based solutions, which do offer simplicity and flexibility in data publishing, but too little in terms of semantic interoperability. We demonstrate the feasibility of this idea through the actual development of a large scale data integration project involving seven ocean science data repositories from five institutions in the U.S. In addition, we make two contributions as part of this dissertation work, which also play crucial roles in the aforementioned data integration project. First, we develop a collection of more than a dozen ontology design patterns that capture the key notions in the ocean science occurring in the participating data repositories. These patterns contain axiomatization of the key notions and were developed with an intensive involvement from the domain experts. Modeling of the patterns was done in a systematic workflow to ensure modularity, reusability, and flexibility of the whole pattern collection. Second, we propose the so-called pattern views that allow data providers to publish their data in very simple intermediate schema and show that they can greatly assist data providers to publish their data without requiring a thorough understanding of the axiomatization of the patterns