Automatic Information Retrieval Research Articles

Application fields of gamification

In the modern period of universal consumer and entertainment psychology of society, interest in gamification is growing. Game components penetrate into all spheres of activity: business, banking, education and even medicine - common trainings, quests aimed at mastering certain skills. The method of typology, aimed at finding stable features and properties of the object under study. Content analysis was involved, in particular, resources with gamified elements were monitored for automated information retrieval (content monitoring). In the course of the research we came to the conclusion that gamification has a significant impact on the life of modern man. The market of gamified technologies is actively developing in Ukraine and the world. Gamification allows the rational use of available resources, so that as a result all parties achieve the goal, but its use should be treated with caution so as not to exacerbate existing contradictions or, conversely, not to demotivate. That is why it is so important to be critical of the use of game elements in each of the spheres, to realize and distinguish the useful potential of the game from the game as an end in itself, which can adversely affect mental and physical health, self-realization in society.

Automated extraction of information from Polish resume documents in the IT recruitment process

The problem of automated information retrieval and semantic analysis becomes more and more popular due to the difficulty of searching and analyzing large text datasets. Also, the recruitment process implies searching vast amounts of usually unstructured text files and makes human analysis challenging or even impossible to perform.This research presents a hybrid approach to automated information retrieval for the recruitment process in the IT industry. The proposed model implements a multi-module system in terms of low resource language dictionaries and complex linguistic dependencies in Polish.The experimental results confirmed our proposed solution. The keyword recognition for different resume sections was 60%-160% higher than for separate common tools.

Development of Information and Reference System on Ecology

The paper substantiates the need to develop an information and reference system for ecology. Since the volume of regulatory and legal information in this area is enormous, and in general, ecology and environmental protection simply cannot be taken into account, there is a need for a fairly prompt and simple search for the information necessary for the user. For this purpose, the main methods of information search are considered and systematized, and an analysis of the main systems for searching for reference and legal information available for general use is carried out. On the basis of the analysis, the advantages and disadvantages of the leading information and reference systems were revealed, which provided the basis for setting tasks for the development of a specialized information and reference system. The introduction shows the relevance of the search and storage of regulatory documents for use in work by persons engaged in ecologic and environmental protection activities. The authors proposed a technique for automatic information retrieval from Internet sources, which consists of the following procedures: searching for the necessary information, processing the information received, obtaining the necessary information, preparing information for loading into the system database, and updating the information. The stages of the system design from the formation of requirements for the system and the implementation of functional modeling to the description of the implementation of each module are shown. The structure of the information and reference system, consisting of modules for processing input information, extracting information, processing output information and a database, is described. When describing the system architecture, the system interface and examples of outputting the results of the parser's operaton are given. Finally, the results of testing the system and the expected benefits of implementation are described. The information and reference system, with certain settings, can be used in other areas of human activity, where it is necessary to search for relevant regulatory information of a certain profile.

Viewing images of foods evokes taste quality-specific activity in gustatory insular cortex

Previous studies have shown that the conceptual representation of food involves brain regions associated with taste perception. The specificity of this response, however, is unknown. Does viewing pictures of food produce a general, nonspecific response in taste-sensitive regions of the brain? Or is the response specific for how a particular food tastes? Building on recent findings that specific tastes can be decoded from taste-sensitive regions of insular cortex, we asked whether viewing pictures of foods associated with a specific taste (e.g., sweet, salty, and sour) can also be decoded from these same regions, and if so, are the patterns of neural activity elicited by the pictures and their associated tastes similar? Using ultrahigh-resolution functional magnetic resonance imaging at high magnetic field strength (7-Tesla), we were able to decode specific tastes delivered during scanning, as well as the specific taste category associated with food pictures within the dorsal mid-insula, a primary taste responsive region of brain. Thus, merely viewing food pictures triggers an automatic retrieval of specific taste quality information associated with the depicted foods, within gustatory cortex. However, the patterns of activity elicited by pictures and their associated tastes were unrelated, thus suggesting a clear neural distinction between inferred and directly experienced sensory events. These data show how higher-order inferences derived from stimuli in one modality (i.e., vision) can be represented in brain regions typically thought to represent only low-level information about a different modality (i.e., taste).

Использование адвокатом информационных технологий при оказании юридической помощи в суде

This article expresses the results of a comprehensive scientific research: 1) classification of information tools used in arbitration and civil proceedings; 2) identified problematic aspects of the use of legal reference systems and automated information retrieval systems, identified the importance of use the automated systems within the lawyer’s request; 3) analyzed the features of the use of videoconferencing systems by a lawyer; 4) the problematic aspect of the preservation of attorney secrecy was found when using EDS within the SAS “Electronic Justice”. The study is based on doctrinal sources (russian and foreign), concepts of the Government of the Russian Federation, intra-judicial administrative acts and corporate norms of the intra-legal community.

Clinical Decision Support for the Diagnosis and Management of Adult and Pediatric Hypertension.

Purpose of ReviewTo review literature from 2016 to 2019 on clinical decision support (CDS) for diagnosis and management of hypertension in children and adults.Recent FindingsTen studies described hypertension CDS systems. Novel advances included the integration of patient-collected blood pressure data, automated information retrieval and management support, and use of CDS in low-resource/developing-world settings and in pediatrics. Findings suggest that CDS increases hypertension detection/control, yet many children and adults with hypertension remain undetected or undercontrolled. CDS challenges included poor usability (from lack of health record integration, excessive data entry requests, and wireless connectivity challenges) and lack of clinician trust in blood pressure measures.SummaryHypertension CDS has improved but not closed gaps in the detection and control of hypertension in children and adults. The studies reviewed indicate that the usability of CDS and the system where CDS is deployed (e.g., commitment to high-quality blood pressure measurement/infrastructure) may impact CDS’s ability to increase hypertension detection and control.

Automatic room information retrieval and classification from floor plan using linear regression model

The automatic creation of a repository of the building’s floor plan helps a lot to the architects to reuse them. The basic approach is to extract and recognize texts, symbols or graphics to retrieve the information of the floor plan from the images. This paper proposes a floor plan information retrieval algorithm. The proposed algorithm is based on shape extraction and room identification. $$\alpha $$ -shape is used for finding an accurate shape. From the detected shapes, actual areas of rooms are calculated. Later, a regression model-based binary room classification model is proposed to classify them into room-type, i.e., bedroom, drawing room, kitchen, and non-room-type, i.e., parking porch, bathroom, study room and prayer room. The proposed model is tested on the CVC-FP dataset with an average room detection accuracy of 85.71% and room recognition accuracy of 88%.

Evaluation of patient-level retrieval from electronic health record data for a cohort discovery task.

ObjectiveGrowing numbers of academic medical centers offer patient cohort discovery tools to their researchers, yet the performance of systems for this use case is not well understood. The objective of this research was to assess patient-level information retrieval methods using electronic health records for different types of cohort definition retrieval.Materials and MethodsWe developed a test collection consisting of about 100 000 patient records and 56 test topics that characterized patient cohort requests for various clinical studies. Automated information retrieval tasks using word-based approaches were performed, varying 4 different parameters for a total of 48 permutations, with performance measured using B-Pref. We subsequently created structured Boolean queries for the 56 topics for performance comparisons. In addition, we performed a more detailed analysis of 10 topics.ResultsThe best-performing word-based automated query parameter settings achieved a mean B-Pref of 0.167 across all 56 topics. The way a topic was structured (topic representation) had the largest impact on performance. Performance not only varied widely across topics, but there was also a large variance in sensitivity to parameter settings across the topics. Structured queries generally performed better than automated queries on measures of recall and precision but were still not able to recall all relevant patients found by the automated queries.ConclusionWhile word-based automated methods of cohort retrieval offer an attractive solution to the labor-intensive nature of this task currently used at many medical centers, we generally found suboptimal performance in those approaches, with better performance obtained from structured Boolean queries. Future work will focus on using the test collection to develop and evaluate new approaches to query structure, weighting algorithms, and application of semantic methods.

Automatic retrieval of network hotspot information based on improved DBSCAN clustering algorithm

With the continuous development of the Internet in the world today, the proliferation of network information makes it difficult for people to effectively screen out current hotspot information. In order to solve the problem of how to retrieve the current hot information quickly and accurately under the massive network information, an automatic network information retrieval method based on the improved DBSCAN clustering algorithm is proposed. The retrieved related keywords are combined to reduce the feature terms, which effectively solves the problem of repeated acquisition of public resource object neighbourhoods, greatly improves the accuracy and efficiency of the clustering algorithm, and realizes automatic retrieval of network information hot spots. The results show that the automatic network information retrieval method based on the improved DBSCAN clustering algorithm proposed in this paper can quickly and accurately find the current information hotspots on the Internet, help users to obtain the hotspot information of their own most interest, and promote the progress and development of the Internet.

Historical document layout analysis using anisotropic diffusion and geometric features

There are several digital libraries worldwide which maintain valuable historical manuscripts. Usually, digital copies of these manuscripts are offered to researchers and readers in raster-image format. These images carry several document degradations that may hinder automatic information retrieval solutions such as manuscript indexing, categorization, retrieval by content, etc. In this paper, we propose a learning-free and hybrid document layout analysis for handwritten historical manuscripts. It has two main phases: page characterization and segmentation. First, the proposed method locates main-content initially using top-down whitespace analysis. It employs anisotropic diffusion filtering to find whitespaces. Then, it extracts template features representing manuscripts’ authors writing behavior. After that, moving windows are used to scan the manuscript page and define main-content boundaries more precisely. We evaluated the proposed method on two datasets: One set is publicly available with 38 historical manuscript pages, and the other set of 51 historical manuscript pages that are collected from the online Harvard Library. Experiments on both datasets show promising results in terms of segmentation quality of main-content that reaches up to 98.5% success rate.

SEPARATE VIEWS ON THE RELATIONSHIP OF SPECIAL TECHNOLOGY OF LAW ENFORCEMENT BODIES AND CRIMINALISTIC TECHNIQUE

The correlation of forensic technology and operational technology among themselves and with special equipment of law enforcement agencies was investigated. It is shown that the constant growth of technical equipment of the law enforcement agencies of Ukraine and the presence of law enforcement structures led to the emergence of independent groups of technical means. It is emphasized that the forensic technique has a special character for its purpose, manifested in the maintenance of the main criminal process to obtain procedural information. It is proved that operational technology, as a section of the theory of operational-search activity and a component of the more general scientific concept of “special technology of law enforcement agencies”, has its own system and correlates with the forensic technique as equivalent categories of legal science. The emergence of a very important means of collecting, accumulating, storing, processing, searching and providing the necessary information is shown - automated information retrieval systems, automated specialized systems and intelligent systems that make up a separate group of special equipment. It is proved that the methodological basis of special equipment is scientifically based tactical techniques, methods and information technology. Special equipment of law enforcement agencies as an interdisciplinary branch of legal science is a system of scientific regulations and recommendations, create conditions for the development of technical tools (forensic, operational, organizational, security), as well as scientifically based methods, techniques and information technology to counter crime law enforcement agencies. The system of special equipment of law enforcement agencies consists of elements that include general provisions and branches of special equipment of law enforcement agencies. Branches of special equipment of law enforcement agencies consist of the main directions of its use in law enforcement, namely: with respect to investigative activities ― forensic technology, operational search activities ― operational technology, administrative activities ― organizational technology. It is proved that the special technique of law enforcement and forensic technology are both common and particular, respectively.

Scattering Key-Frame Extraction for Comprehensive VideoSAR Summarization: A Spatiotemporal Background Subtraction Perspective

Video synthetic aperture radar (VideoSAR) presents significant potential to enhance the performance of automatic information retrieval and interpretation in the dynamic region of interest (DROI). Key-frame extraction represents effective contents in processing massive video data. In this article, a novel computer vision-based background subtraction perspective is proposed for automatic VideoSAR scattering key-frame selection. A universal parameterization scattering key-frame model is firstly investigated, which serves to reveal the VideoSAR scattering key frames. Then, a spatiotemporal scattering extractor, called the subaperture energy gradient (SEG), together with a modified statistical and knowledge-based object tracker (MSAKBOT) is proposed to robustly discriminate the scattering key-frame state of the alternation between transient persistence and disappearance. The proposed SEG-MSAKBOT method presents a more comprehensive measurement of scattering key frames that is adaptive to the multitemporal video sequences effectively. Finally, experimental results and performance assessment conducted on two real airborne VideoSAR data with the coherent integration angles of 21° and 27° demonstrate that the proposed perspective is robust and reliable to capture scattering key frames and video content summarization with highly accurate descriptions in various DROIs.

An Information Retrieval Approach to ICD-10 Classification.

ICD-10 (International Classification of Diseases 10th revision) is a classification code for diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases. This paper describes an automatic information retrieval approach to map free-text disease descriptions to ICD-10 codes. We use the Hospital Italiano de Buenos Aires (HIBA) terminology data mapped to ICD-10 codes as indexed data to find an appropriate ICD-10 code using search engine similarity metrics.

Classification Scheme for Incident Reports of Medication Errors.

This study aimed to develop a classification scheme for retrieving information from incident reports of medication errors. This 15-category classification scheme captures minimal medication-incident related information from incident reports and thus serves as an information model for automatic information retrieval solution. The automatic solution uses recent advances in artificial intelligence methods to learn from incident report resources and is promising to the prevention of adverse drug events and promotion of safety in medical care.

A Concise Review of Named Entity Recognition System: Methods and Features

Named Entity Recognition (NER) is an elementary tool for all application areas in Natural Language Processing (NLP) such as Automatic Summarization, Information Extraction, Information Retrieval, Text Mining, Machine Translation, Question Answering, and Genetics. NER is a task to discover and categorises the named entities (‘atomic elements’) in the text into predefined classes such as the names of persons, organizations, locations, terminologies of time, quantity and etc. Different languages may have different morphologies and thus involve dissimilar NER procedures. For example, an Arabic NER system cannot be practically used in processing Malay texts due to the different morphological features. The morphological features of every language are rich and complex and donates to the difficulties of implementing an actual method to develop the accurate NER system. In this paper, we review on three main techniques that commonly used to develop an NER system well-known as Rule-Based, Machine Learning, and Hybrid approach. This paper also highlights the features of each technique.

THE GENESIS OF APPLYING IT TECHNOLOGIES IN PROPHYLAXIS AND CRIME INVESTIGATION USING FIREWORKS

In the article, on the basis of the analysis of scientific literature and expert practice, the question of the use of modern information technologies in the prevention and investigation of crimes committed with the use of firearms is disclosed. The emphasis is placed on the fact that today in Ukraine due to the large number of crimes involving firearms, which has not significantly decreased in comparison with previous years, the issue of the introduction of modern IT technologies into expert work remains relevant, including the field of expertise of weapons and ballistic record keeping. As a result of studying the experience of using IT-technologies in this industry in Ukraine, existing problems and certain ways of their solution are outlined. Among such problems it is necessary to note: firstly, the very slow introduction of ballistic systems by Ukrainian expert divisions. Today, these systems have a relatively small number of expert departments. Others continue to carry out identification tests in manual mode, do not mention the operational checking of records; secondly, the identification systems which used by expert units in Ukraine, in the vast majority, are, nevertheless, automatized, and not information retrieval, which in turn prevents the creation of a single data bank of image surfaces of bullets and sleeves with the subsequent automatic search. Thereafter, it is quite difficult to carry out inspections for the existing collection of bullets and cartridges in operational mode. To solve these issues, it is necessary: firstly, if possible, to create its own automated information retrieval identification ballistic system which can be made on the basis of existing domestic automated ballistic systems, to implement it in the practical activities of all regional expert departments; second, to develop a single application software that would allow creating a single data bank of images of ballistic nature objects; thirdly, to ensure the interconnection and exchange of information between regional and central databases, and to ensure the protection of information from unauthorized interference; fourthly, to organize the training of relevant personnel and their studying. Key words: genesis, prevention, crime investigation, IT technology, firearms.

A Survey on Information Retrieval System for Authenticating a Tweet

With the growing needs and population, there is tremendous increase in volume of data produced each and every hour. Social sites like Twitter, Facebook etc., produce incredible amount of data and information which are blogs i.e. tweets which are written and updated every minute and second. With this growing data, a need for an Information retrieval system is seen, wherein the essential information or data can be identified and retrieved easily from large databases. Th e collection of information from relevant information resources is Information retrieval system. It is a science of searching data or information in documents also finding documents and also metadata from databases images, text or sounds. As very less search has been done in this field, a need for automated information retrieval system is seen, wherein searching of these documents and information can been done automatically or say using machine learning. In this paper, we proposed a model that will gather data from twitter, in the form of tweets and find whether the given tweet is fake or un fake i.e. spam or not. We will use machine learning algorithms and develop an IR model for it. Our proposed system would be more efficient than the traditions IR models

Recovering Damaged Documents to Improve Information Retrieval Processes

Although computer forensics is frequently related to the investigation of computer crimes, it can also be used in civil procedures. An example of case of use is information retrieval from damaged documents, where words have undergone alterations, either accidentally or intentionally. In this paper, we present a new tool able to retrieve information from large volumes of documents whose contents have been damaged. We have designed a new approach to recover the original words, composed of two stages: a text cleaning filter, able to remove non relevant information, and a text correction unit, which gather a general purpose spell checker with a N-gram based spell checker built specifically for the domain of the documents. The benefits of using this combined approach are two-fold: on the one hand, the general spell checker allows us to leverage all the general purpose techniques that are usually used to perform the corrections; on the other hand, the use of an N-gram based model allows us to adapt them to the particular domain we are tackling exploiting text regularities detected in successfully processed domain documents. The result of the correction allows us to improve automatic information retrieval tasks of from the texts. We have tested it using a real data set by using an information extraction tool based on semantic technologies in collaboration with the Spanish company InSynergy Consulting.

Olga Pankratievna Teslenko, the Enthusiast and Innovator of Scientific Research: to the 50th Anniversary of the First Edition of the Library Bibliographic Classification

The article examines the biography of Olga Pankratieva Teslenko (1911—1974), the eminent library scientist, developer and the first chief editor of the Library bibliographic classification (LBC). Her name is inextricably linked with the history of the national Library bibliographic classification and introduction of LBC in the practice of libraries.The purpose of the article is to reveal the significance of personality of the scientific supervisor in the formation of potential of sustainable development of the national classification system, ensuring its fundamental nature, comprehensiveness and integrity at all stages of the LBC development.The completion of publication of LBC schedules for scientific libraries (1960—1968) became an outstanding event in the national library science. Theoretical development of the LBC was most fully reflected in the Introduction to the Classification and in the numerous articles published in special periodicals. There were formulated theoretical and philosophical principles of LBC construction, substantiated the sequence of the main classes, the principles of classification of sciences. O.P. Teslenko has developed the priority table of LBC index signs for their automatic ordering. O.P. Teslenko made significant contribution to the study of issues related to the use of LBC as a language for automated information search. She carried out a lot of work on the analysis of LBC schedules in the light of the requirements of the automated information retrieval system (IRS) and developed the program of schedule optimization. As scientific supervisor, O.P. Teslenko created organizational structure for coordinating activity with the largest libraries of the country, their interaction with scientific and branch institutions and organizations cooperating in the development of the national classification.O.P. Teslenko’s articles on LBC, published in press, have found the response abroad, were translated into many languages and still serve as a source of theoretical and methodological basis in research studies on classification of sciences and library and information activities.

A Fuzzy Logic Based Synonym Resolution Approach for Automated Information Retrieval

Precise semantic similarity measurement between words is vital from the viewpoint of many automated applications in the areas of word sense disambiguation, machine translation, information retrieval and data clustering, etc. Rapid growth of the automated resources and their diversified novel applications has further reinforced this requirement. However, accurate measurement of semantic similarity is a daunting task due to inherent ambiguities of the natural language, spread of web documents across various domains, localities and dialects. All these issues render to the inadequacy of the manually maintained semantic similarity resources (i.e. dictionaries). This article uses context sets of the words under consideration in multiple corpora to compute semantic similarity and provides credible and verifiable semantic similarity results directly usable for automated applications in the intelligent manner using fuzzy inference mechanism. It can also be used to strengthen the existing lexical resources by augmenting the context set and properly defined extent of semantic similarity.