Intuitive justifications of medical semantic search results

2014 ◽  
Vol 30 ◽  
pp. 1-17 ◽  
Author(s):  
Björn Forcher ◽  
Thomas Roth-Berghofer ◽  
Stefan Agne ◽  
Andreas Dengel
Keyword(s):  
Semantic Search ◽  
Search Results

scholarly journals PENERAPAN METODE SEMANTIK SEARCH DALAM SISTEM INFORMASI PENCARIAN DOKUMEN KERJA PRAKTEK DAN SKRIPSI BERBASIS WEB

2018 ◽  
Vol 3 (2) ◽  
pp. 83-88
Author(s):  
Mitra Unik
Keyword(s):  
Computer Science ◽  
Search Method ◽  
Semantic Search ◽  
Practical Work ◽  
Web Based ◽  
Engineering Faculty ◽  
Search Results

This writing discusses the making of the application search documents practical work and thesis in the Department of Informatics Engineering Faculty of Computer Science Univestias Muhammadiyah Riau. This web-based application uses semantic search method in its search results. This app is designed to generate relevant or easy-to-understand search words by students and also generate words related to search keywords. The goal is to facilitate students in finding reference documents working practice and thesis and to avoid similarity with the previous student topic.

Construction of the structural definition-based terminology ontology system and semantic search evaluation

2016 ◽  
Vol 34 (4) ◽  
pp. 705-732 ◽  
Author(s):  
Young Man Ko ◽  
Min Sun Song ◽  
Seung Jun Lee
Keyword(s):  
Keyword Search ◽  
Relevant Information ◽  
Semantic Search ◽  
Research Papers ◽  
Inference Control ◽  
Content Type ◽  
Search Results ◽  
Input Ratio ◽  
Structural Definition ◽  
Term Data

Purpose The purpose of this paper is to construct a structural definition-based terminology ontology system that defines the meanings of academic terms on the basis of properties and links terms with properties that are structured by conceptual categories (classes). This study also aims to test the possibility of semantic searches by generating inference rules and setting very complicated search scenarios. Design/methodology/approach For the study, 55,236 keywords from the articles of the “Korea Citation Index” were structurally defined and relationships among terms and properties were built. Then, the authors converted the RDB data into RDF and designed ontologies using the ontology developing tool Protégé. The authors also tested the designed ontology with the inference engine of the Protégé editor. The generated reference rules were tested by TBox and SPARQL queries. Findings The authors generated inference control rules targeting high-input-ratio data in the properties of classes by calculating the input ratio of real input data in the system, and then the authors executed a semantic search by SPARQL query by setting very complicated search scenarios, for which it would be difficult to deduce results via a simple keyword search. As a result, it was confirmed that the search results show the logical combination of semantically related term data. Practical implications The proposed terminology ontology system was constructed with the author keywords from research papers, it will be useful in searching the research papers which include the keywords as search results by the complex combination of semantic relation. And the Structural Terminology Net database could be utilized as an index database in retrieval services and the mining of informal big data through the application of well-defined semantic concepts to each term. Originality/value This paper presented a methodology for supporting IR using expanded queries based on a novel model of structural terminology-based ontology. The user who wants to access the specific topic can create query that brings the semantically relevant information. The search results show the logical combination of semantically related term data, which would be difficult to deduce results via traditional IR systems.

scholarly journals Onto Semantic Tourism Information Retrieval

2018 ◽  
Vol 7 (4.7) ◽  
pp. 148 ◽  
Author(s):  
Shilpa S. Laddha ◽  
Dr. Pradip M. Jawandhiya
Keyword(s):  
Information Retrieval ◽  
Significant Role ◽  
Semantic Search ◽  
Efficient Search ◽  
Domain Specific ◽  
Search Results ◽  
User Query ◽  
Tourism Information ◽  
Relationship Of ◽  
The Relationship

Semantic Search is an area of research which focuses on meaning of terms used in user query. Ontology plays significant role to define the concept and the relationship of terms in domain. Since the understanding of concepts is domain specific, Ontology creation is also domain specific. According to this argument, query interpreted in Tourism domain can have different meaning in some other domain. This paper presents a prototype of information retrieval interface using ontology which can save users time by rendering relevant, precise and efficient search results as compared to traditional search interfaces.  

GSSP – A Generic Semantic Search Platform

2015 ◽  
pp. 220-239
Author(s):  
Sara Paiva ◽  
Manuel Ramos-Cabrer ◽  
Alberto Gil-Solla
Keyword(s):  
Quality Management ◽  
Search Engines ◽  
Management System ◽  
Quality Management System ◽  
Semantic Search ◽  
Search System ◽  
Search Results ◽  
Ongoing Work ◽  
Specific Goal

Semantic search has been rapidly growing as a way to improve search results. The meaning of the input expression has revealed to produce better results than the traditional keyword appearance. Regarding search engines, there are currently several proposals but all of them are already implemented to a specific goal. We find important to develop a generic semantic search system so it rapidly be adapted to any system and domain that has search needs. This work introduces GSSP, a generic semantic search platform proposal. We present the platform and the several steps that need to be followed in order for the platform to be used. We also provide the ongoing work that is being done to apply GSSP to a Quality Management System.

Construction of metadata database structured by conceptual elements of text structure and semantic search evaluation of Korean studies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Young Man Ko ◽  
Min Sun Song ◽  
Seung Jun Lee
Keyword(s):  
Keyword Search ◽  
Search Algorithm ◽  
Interdisciplinary Studies ◽  
Text Structure ◽  
Semantic Search ◽  
Research Articles ◽  
Content Type ◽  
Search Results ◽  
Korean Studies ◽  
Data Points

Purpose This study aims to develop metadata of conceptual elements based on the text structure of research articles on Korean studies, to propose a search algorithm that reflects the combination of semantically relevant data in accordance with the search intention of research paper and to examine the algorithm whether there is a difference in the intention-based search results. Design/methodology/approach This study constructed a metadata database of 5,007 research articles on Korean studies arranged by conceptual elements of text structure and developed F1(w)-score weighted to conceptual elements based on the F1-score and the number of data points from each element. This study evaluated the algorithm by comparing search results of the F1(w)-score algorithm with those of the Term Frequency- Inverse Document Frequency (TF-IDF) algorithm and simple keyword search. Findings The authors find that the higher the F1(w)-score, the closer the semantic relevance of search intention. Furthermore, F1(w)-score generated search results were more closely related to the search intention than those of TF-IDF and simple keyword search. Research limitations/implications Even though the F1(w)-score was developed in this study to evaluate the search results of metadata database structured by conceptual elements of text structure of Korean studies, the algorithm can be used as a tool for searching the database which is a tuning process of weighting required. Practical implications A metadata database based on text structure and a search method based on weights of metadata elements – F1(w)-score – can be useful for interdisciplinary studies, especially for semantic search in regional studies. Originality/value This paper presents a methodology for supporting IR using F1(w)-score—a novel model for weighting metadata elements based on text structure. The F1(w)-score-based search results show the combination of semantically relevant data, which are otherwise difficult to search for using similarity of search words.

scholarly journals Semantic Search and Summarization of Judgments Using Topic Modeling

2021 ◽  
Author(s):  
Tien-Hsuan Wu ◽  
Ben Kao ◽  
Felix Chan ◽  
Anne SY Cheung ◽  
Michael MK Cheung ◽  
...  
Keyword(s):  
Topic Modeling ◽  
Domain Knowledge ◽  
Semantic Search ◽  
User Evaluation ◽  
Legal Research ◽  
Legal Professionals ◽  
Search Results ◽  
User Query ◽  
Salient Points ◽  
Legal Document

Online legal document libraries, such as WorldLII, are indispensable tools for legal professionals to conduct legal research. We study how topic modeling techniques can be applied to such platforms to facilitate searching of court judgments. Specifically, we improve search effectiveness by matching judgments to queries at semantics level rather than at keyword level. Also, we design a system that summarizes a retrieved judgment by highlighting a small number of paragraphs that are semantically most relevant to the user query. This summary serves two purposes: (1) It explains to the user why the machine finds the retrieved judgment relevant to the user’s query, and (2) it helps the user quickly grasp the most salient points of the judgment, which significantly reduces the amount of time needed by the user to go through the returned search results. We further enhance our system by integrating domain knowledge provided by legal experts. The knowledge includes the features and aspects that are most important for a given category of judgments. Users can then view a judgement’s summary focusing on particular aspects only. We illustrate the effectiveness of our techniques with a user evaluation experiment on the HKLII platform. The results show that our methods are highly effective.

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