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.

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.  

scholarly journals A semantic search approach for hyper relational knowledge graphs

2021 ◽  
Author(s):  
Veronica dos Santos ◽  
Sérgio Lifschitz
Keyword(s):  
Information Retrieval ◽  
Semantic Search ◽  
Similarity Function ◽  
Search Results ◽  
Relational Knowledge ◽  
Retrieval Systems ◽  
User Query ◽  
Information Retrieval Systems ◽  
Knowledge Graphs ◽  
Search Approach

Information Retrieval Systems usually employ syntactic search techniques to match a set of keywords with the indexed content to retrieve results. But pure keyword-based matching lacks on capturing user's search intention and context and suffers of natural language ambiguity and vocabulary mismatch. Considering this scenario, the hypothesis raised is that the use of embeddings in a semantic search approach will make search results more meaningfully. Embeddings allow to minimize problems arising from terminology and context mismatch. This work proposes a semantic similarity function to support semantic search based on hyper relational knowledge graphs. This function uses embeddings in order to find the most similar nodes that satisfy a user query.

Classification of means and methods of the Web semantic retrieval

2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Search Engines ◽  
Domain Knowledge ◽  
Information Needs ◽  
Web Search ◽  
User Interaction ◽  
Query Languages ◽  
Semantic Search ◽  
Semantic Retrieval ◽  
The Web

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

scholarly journals Modeling Human Factors Topics in Aviation Reports

2019 ◽  
Vol 63 (1) ◽  
pp. 126-130
Author(s):  
Beth Lyall-Wilson ◽  
Nicolas Kim ◽  
Elizabeth Hohman
Keyword(s):  
Human Factors ◽  
Topic Modeling ◽  
Domain Knowledge ◽  
Aviation Safety ◽  
Subject Matter Experts ◽  
Text Data ◽  
Modeling Approach ◽  
Modeling Process ◽  
Manual Review ◽  
Initial Extraction

This paper describes the development and new application of a text modeling process for identifying human factors topics, such as fatigue, workload, and distraction in aviation safety reports. Current approaches to identifying human factors topic representations in text data rely on manual review from subject matter experts. The implementation of a semi-supervised text modeling method overcomes the need for lengthy manual review through an initial extraction of pre-defined human factors topics, freeing time for focus on analyzing the information. This modeling approach allows analysts to use keywords to define topics of interest up front and influence the convergence of the model toward a result that reflects them, which provides an advantage over classic topic modeling approaches where domain knowledge is not integrated into the generation of derived topics. This paper includes a description of the modeling approach and rationale, data used, evaluation methods, challenges, and suggestions for future applications.

scholarly journals Visit to the Faculty of Law in the University of Jos, Nigeria

2007 ◽  
Vol 7 (1) ◽  
pp. 17-19 ◽  
Author(s):  
Gerry Power
Keyword(s):  
The Internet ◽  
Legal Research ◽  
Legal Professionals ◽  
Law Faculty ◽  
The Law ◽  
The University

Gerry Power was invited to go to the University of Jos in April 2006 to present workshops to the Law Faculty and other interested legal professionals on using the internet for legal research. He writes about his experiences in dealing with running online workshops whilst coping with electricity shortages and the incredible experience of Nigeria!

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.

scholarly journals An Art of Review on Conceptual based Information Retrieval

Webology ◽  
2021 ◽  
Vol 18 (SI02) ◽  
pp. 21-31
Author(s):  
P. Mahalakshmi ◽  
N. Sabiyath Fathima
Keyword(s):  
Information Retrieval ◽  
Keyword Search ◽  
Semantic Representation ◽  
Research Work ◽  
Semantic Search ◽  
Future Research ◽  
Conceptual Information ◽  
Retrieval Systems ◽  
User Query ◽  
Information Retrieval Systems

Basically keywords are used to index and retrieve the documents for the user query in a conventional information retrieval systems. When more than one keywords are used for defining the single concept in the documents and in the queries, inaccurate and incomplete results were produced by keyword based retrieval systems. Additionally, manual interventions are required for determining the relationship between the related keywords in terms of semantics to produce the accurate results which have paved the way for semantic search. Various research work has been carried out on concept based information retrieval to tackle the difficulties that are caused by the conventional keyword search and the semantic search systems. This paper aims at elucidating various representation of text that is responsible for retrieving relevant search results, approaches along with the evaluation that are carried out in conceptual information retrieval, the challenges faced by the existing research to expatiate requirements of future research. In addition, the conceptual information that are extracted from the different sources for utilizing the semantic representation by the existing systems have been discussed.

Indian Judgment Categorization for Practicing Similar Judgment Identification

2021 ◽  
pp. 232-241
Author(s):  
Jenish Dhanani ◽  
Rupa G. Mehta ◽  
Dipti P. Rana ◽  
Rahul Lad ◽  
Amogh Agrawal ◽  
...  
Keyword(s):  
Search Space ◽  
Automated System ◽  
Court Case ◽  
Criminal Cases ◽  
Legal Information ◽  
Law System ◽  
Legal Professionals ◽  
Related Information ◽  
Legal Document ◽  
Legal Domain

Recently, legal information retrieval has emerged as an essential practice for the legal fraternity. In the legal domain, judgment is a specific kind of legal document, which discusses case-related information and the verdict of a court case. In the common law system, the legal professionals exploit relevant judgments to prepare arguments. Hence, an automated system is a vital demand to identify similar judgments effectively. The judgments can be broadly categorized into civil and criminal cases, where judgments with similar case matters can have strong relevance compared to judgments with different case matters. In similar judgment identification, categorized judgments can significantly prune search space by restrictive search within a specific case category. So, this chapter provides a novel methodology that classifies Indian judgments in either of the case matter. Crucial challenges like imbalance and intrinsic characteristics of legal data are also highlighted specific to similarity analysis of Indian judgments, which can be a motivating aspect to the research community.

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.

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