MEDREADFAST: A structural information retrieval engine for big clinical text

Technology development has affected many areas of life, especially the entertainment field. One of the fastest growing entertainment industry is anime. Anime has evolved as a trend and a hobby, especially for the population in the regions of Asia. The number of anime fans grow every year and trying to dig up as much information about their favorite anime. Therefore, a chatbot application was developed in this study as anime information retrieval media using regular expression pattern matching method. This application is intended to facilitate the anime fans in searching for information about the anime they like. By using this application, user can gain a convenience and interactive anime data retrieval that can’t be found when searching for information via search engines. Chatbot application has successfully met the standards of information retrieval engine with a very good results, the value of 72% precision and 100% recall showing the harmonic mean of 83.7%. As the application of hedonic, chatbot already influencing Behavioral Intention to Use by 83% and Immersion by 82%. Index Terms—anime, chatbot, information retrieval, Natural Language Processing (NLP), Regular Expression Pattern Matching

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Coding structural information in information retrieval systems with large banks of organic compounds

Pharmaceutical Chemistry Journal ◽

10.1007/bf00778119 ◽

1979 ◽

Vol 13 (5) ◽

pp. 503-507

Author(s):

E. S. Polishchuk

Keyword(s):

Information Retrieval ◽

Organic Compounds ◽

Structural Information ◽

Retrieval Systems ◽

Information Retrieval Systems

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Разрешение стрелочной омонимии в конструкциях с сирконстантами средствами онтологической семантики

Компьютерная лингвистика и вычислительные онтологии ◽

10.17586/2541-9781-2020-4-73-82 ◽

2020 ◽

pp. 73-82

Author(s):

Алина Андреевна Захарова

Keyword(s):

Artificial Intelligence ◽

Information Retrieval ◽

Retrieval Engine

В статье описывается экспериментальное исследование метода разрешения синтаксической неоднозначности в конструкциях с сирконстантами с помощью онтологической семантики на основе универсального лингвистического процессора AIIRE (Artificial Intelligence Information Retrieval Engine). Выявлены четыре типа неоднозначных конструкций с сирконстантами, и составлены соответствующие поисковые запросы в Национальный корпус русского языка (НКРЯ). В результате получен список из 200 неоднозначных конструкций. Неоднозначность в конструкциях устраняется путем автоматического разбора и последующего ручного выбора его правильных вариантов. Однако на этом этапе возможны следующие проблемы: «разрывы» внутри конструкций, которые обозначают отсутствие нужных семантических связей внутри конструкции, а также большое количество вариантов синтаксического анализа, называемое комбинаторным взрывом. Эти проблемы решаются с помощью таких инструментов AIIRE, как Ontohelper и онтология. Онтология используется для обработки языковых данных и понимается как набор лексических значений или понятий и отношений между ними. Ontohelper – это вспомогательный инструмент с интерфейсом редактирования, где можно моделировать и задавать с помощью онтологическихотношенийвалентностиглаголов. В результате получаются корректные разборы для 66/200 конструкций, и обосновывается,чтоэффективностьданногометодазависитоткачестваиправильностимоделированияпонятийвонтологии.

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Human-Centred Web Search

Next Generation Search Engines ◽

10.4018/978-1-4666-0330-1.ch010 ◽

2012 ◽

pp. 217-238 ◽

Cited By ~ 4

Author(s):

Orland Hoeber

Keyword(s):

Information Retrieval ◽

Decision Support ◽

Search Engine ◽

Information Needs ◽

Web Search ◽

Active Role ◽

Simple Fact ◽

Search Results ◽

Retrieval Engine ◽

The Web

People commonly experience difficulties when searching the Web, arising from an incomplete knowledge regarding their information needs, an inability to formulate accurate queries, and a low tolerance for considering the relevance of the search results. While simple and easy to use interfaces have made Web search universally accessible, they provide little assistance for people to overcome the difficulties they experience when their information needs are more complex than simple fact-verification. In human-centred Web search, the purpose of the search engine expands from a simple information retrieval engine to a decision support system. People are empowered to take an active role in the search process, with the search engine supporting them in developing a deeper understanding of their information needs, assisting them in crafting and refining their queries, and aiding them in evaluating and exploring the search results. In this chapter, recent research in this domain is outlined and discussed.

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Using an Intelligent Agent to Enhance Search Engine Performance

First Monday ◽

10.5210/fm.v2i3.517 ◽

1997 ◽

Cited By ~ 8

Author(s):

James Jansen

Keyword(s):

Information Retrieval ◽

Intelligent Agents ◽

Engine Performance ◽

Relevant Information ◽

Current Status ◽

Short Term ◽

Short Summary ◽

Retrieval Engine ◽

Personal Assistants ◽

Search And Retrieval

The amount of information available via networks and databases has rapidly increased and continues to increase. Existing search and retrieval engines provide limited assistance to users in locating the relevant information that they need. Autonomous, intelligent agents may prove to be the needed item in transforming passive search and retrieval engines into active, personal assistants. This proposal explores the quantity of information available that is driving the need for improved search and retrieval engines. It then reviews current information retrieval literature and agency literature. Following these reviews, it proposes that the combination of effective information retrieval techniques and autonomous, intelligent agents can improve the performance of short-term information retrieval in an existing search or retrieval engine. A review of the current status of agents in various areas including information retrieval is also presented. The proposal then presents the objectives of this research, the methodology to achieve these objectives, and concludes with the contributions of this research and a short summary.

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Towards a multimedia World-Wide Web information retrieval engine

Computer Networks and ISDN Systems ◽

10.1016/s0169-7552(97)00046-9 ◽

1997 ◽

Vol 29 (8-13) ◽

pp. 1181-1191 ◽

Cited By ~ 16

Author(s):

Sougata Mukherjea ◽

Kyoji Hirata ◽

Yoshinori Hara

Keyword(s):

Information Retrieval ◽

World Wide Web ◽

World Wide ◽

Web Information Retrieval ◽

Web Information ◽

Retrieval Engine

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Automated Subsurface Knowledge ASK Thamama Retrieval Engine Driven by Conversational Text Analytics and NLP - Lessons Learned in Managing Large Volume of Documents in Abu Dhabi Assets

10.2118/206372-ms ◽

2021 ◽

Author(s):

Fahed Mubarak Braik ◽

Abdulla Sulaiman Al Shehhi ◽

Luigi Saputelli ◽

Carlos Mata ◽

Dorzhi Badmaev ◽

...

Keyword(s):

Information Retrieval ◽

Natural Language ◽

Language Processing ◽

Text Processing ◽

Lessons Learned ◽

Text Analytics ◽

Data Set ◽

Data Repositories ◽

Retrieval Engine ◽

Engine Concept

Abstract The purpose of this paper is to communicate the experiences in the development of an innovative concept named "ASK Thamama" as an automated data and information retrieval engine driven by artificial intelligence techniques including text analytics and natural language processing. ASK is an AI enabled conversational search engine used to retrieve information from various internal data repositories using natural language queries. The text processing and conversational engine concept is built upon available open-source software requiring minimum coding of new libraries. A data set with 1000 documents was used to validate key functionalities with an accuracy of 90% of the search queries and able to provide specific answers for 80% of queries framed as questions. The results of this work show encouraging results and demonstrate value that AI-enabled methodologies can provide natural language search by enabling automated workflows for data information retrieval. The developed AI methodology has tremendous potential of integration in an end-to-end workflow of knowledge management by utilizing available document repositories to valuable insights, with little to no human intervention.

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A Scalable Real Time Agent-Based Information Retrieval Engine

International Journal of Software Innovation ◽

10.4018/ijsi.292022 ◽

2022 ◽

Vol 10 (1) ◽

pp. 0-0

Keyword(s):

Information Retrieval ◽

Web Documents ◽

Distributed Information ◽

Agent Based ◽

Retrieval Systems ◽

Main Challenge ◽

Combination Scheme ◽

Information Retrieval Systems ◽

Information Stream ◽

Retrieval Engine

In distributed information retrieval systems, information in web should be ranked based on a combination of multiple features. Linear combination of ranks has been the dominant approach due to its simplicity and efficiency. Such a combination scheme in distributed infrastructure requires that ranks in resources or agents are comparable to each other. The main challenge is how to transform the raw rank values of different criteria appropriately to make them comparable before any combination. In this manuscript, we will demonstrate how to rank Web documents based on its resource-provided information stream and how to combine and incorporate several raking schemas in one time. The system was tested on the queries provided by a Text Retrieval Conference (TREC), and our experimental results showed that it is robust and efficient compared with similar platforms that used offline data resources.

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