Finding Relevant Information Research Articles

Integration of Convolutional Neural Networks and Recurrent Neural Networks for Foliar Disease Classification in Apple Trees

Automated methods intended for image classification have become increasingly popular in recent years, with applications in the agriculture field including weed identification, fruit classification, and disease detection in plants and trees. In image classification, convolutional neural networks (CNN) have already shown exceptional results but the problem with these models is that these models cannot extract some relevant image features of the input image. On the other hand, the recurrent neural network (RNN) can fully exploit the relationship among image features. In this paper, the performance of combined CNN and RNN models is evaluated by extracting relevant image features on images of diseased apple leaves. This article suggested a combination of pre-trained CNN network and LSTM, a particular type of RNN. With the use of transfer learning, the deep features were extracted from several fully connected layers of pre-trained deep models i.e. Xception, VGG16, and InceptionV3. The extracted deep features from the CNN layer and RNN layer were concatenated and fed into the fully connected layer to allow the proposed model to be more focused on finding relevant information in the input data. Finally, the class labels of apple foliar disease images are determined by the integrated model for apple foliar disease classification, experimental findings demonstrate that the proposed approach outperforms individual pre-trained models.

I Know What You Need: Investigating Document Retrieval Effectiveness with Partial Session Contexts

Reducing user effort in finding relevant information is one of the key objectives of search systems. Existing approaches have been shown to effectively exploit the context from the current search session of users for automatically suggesting queries to reduce their search efforts. However, these approaches do not accomplish the end goal of a search system—that of retrieving a set of potentially relevant documents for the evolving information need during a search session. This article takes the problem of query prediction one step further by investigating the problem of contextual recommendation within a search session. More specifically, given the partial context information of a session in the form of a small number of queries, we investigate how a search system can effectively predict the documents that a user would have been presented with had he continued the search session by submitting subsequent queries. To address the problem, we propose a model of contextual recommendation that seeks to capture the underlying semantics of information need transitions of a current user’s search context. This model leverages information from a number of past interactions of other users with similar interactions from an existing search log. To identify similar interactions, as a novel contribution, we propose an embedding approach that jointly learns representations of both individual query terms and also those of queries (in their entirety) from a search log data by leveraging session-level containment relationships. Our experiments conducted on a large query log, namely the AOL, demonstrate that using a joint embedding of queries and their terms within our proposed framework of document retrieval outperforms a number of text-only and sequence modeling based baselines.

Examination of Health Information Needs of Caregivers of and Individuals with Burn Injuries.

Burns are a leading cause of trauma worldwide with about 450,000 burn injuries being treated at medical facilities in the United States each year. Finding relevant information on the long-term consequences of burn injuries is a significant challenge for many individuals with burn injuries and their caregivers. This qualitative study aimed to identify how individuals with burn injuries and caregivers of individuals with burn injuries prefer to access and use health information, identify obstacles to accessing useful information, and identify information most needed by burn survivors and caregivers. Participants were recruited through hospital listservs, websites, social media, and word of mouth from across the United States. Semi-structured interviews were conducted with 23 individuals, 12 with burn injuries and 11 caregivers of individuals with burn injuries. Three specific needs were identified: (1) more direction from health professionals in finding health information relevant to burn injuries; (2) more internet-based access points that connect individuals to appropriate support networks; and (3) more support for long-term consequences of burn injuries, specifically with psychological, social, and other chronic physical issues. Participants identified various needs in finding relevant health information, thereby highlighting gaps in current literature and the dissemination of current literature. One potential way to address these deficiencies is to consider user-centered design principles in developing research, by more directly involving individuals with burn injuries and caregivers as part of the research team.

PENGARUH KEGIATAN PENGAJIAN REMAJA MAJELIS TAKLIM “NURUL ILMI” DAN KONTRIBUSINYA TERHADAP PEMBENTUKAN AKHLAK GENERASI MUDA (Studi Kasus di Desa Kersana Kec. Kersana Kab. Brees)

This study aims to determine the Model of Superior Madrasah Development and Supporting Elements of Superior Madrasah Development. This study uses a library research method by collecting a number of books, magazines, journals, lifets relating to the problem and research objectives. Collecting data with the results of previous studies that support data on the research theme designing a madrasa education management development model with the research process starting with the stages of identifying, finding relevant information, analyzing the findings, and then developing and expressing them into new findings related to the education management development model. at the madrasa. The key to building a superior madrasah must meet several criteria, namely the availability of professional education personnel, complete facilities and infrastructure, a modern, transparent and democratic professional management system, and a curriculum that is in accordance with the needs of society and the challenges of the modern world. In addition, madrasas also need to pay attention to continuously improve quality, develop innovation and creativity, and build a network of cooperation (networking), so that inputs and outputs are good. In other words, developing superior madrasas requires effective and functional carrying capacity, such as superior human resources, infrastructure (representative study rooms, libraries and laboratories), supporting facilities (boarding/ma'had, mosque or prayer room). Excellent madrasah must be designed according to the vision-mission and institutional objectives, analyze the needs of the academic and institutional system, and understand the geographical and cultural context. Meanwhile, its development requires togetherness and a collective mindset, continuous innovation, and utilizing information technology, building open and principled leadership, improving the quality of madrasa governance, improving the quality of the new student recruitment system, increasing the quantity and quality of extracurricular activities, and improving the quality of the extracurricular activities. teaching and professional development activities.

Describing the Web in less than 140 Characters

Links curation, that is, finding relevant information within the World-Wide-Web and its ever-growing amount of content is a crucial problem for information access. Hyperlinks recommendation has been for a long time a common way to share references between web users, be it by e-mail exchanges, instant messages or forums. We explore in this paper how Social Media extend this recommendation practice by focusing on the citation of hyperlinks on Twitter. We investigate how people deal with the strong limitation of 140 characters per message, showing that this constraint encourages people to perform a good synthesis of the content they are linking to. We take advantage of this practice to efficiently cluster the actual content of the linked pages with an algorithm based on lexical proximities between messages. Our method yields topical clusters that are consistent with the dynamics of user interests with no need to extract text from the pages themselves.

Coronavirus-related health literacy and perceived restrictiveness of protective measures among community-dwelling older persons in Finland

BackgroundOlder people with limited health literacy may encounter difficulties in finding relevant information on COVID-19, understanding its relevance, and complying with recommended protective measures. Complying with such recommendations has required older as well as younger persons to change their daily lives in ways that have reduced their opportunities for engaging in many activities meaningful to them.AimsTo find out from what sources older people have obtained information on protective measures, the level of their coronavirus-related health literacy (CHL), and whether CHL is associated with their perceptions of the restrictiveness of coronavirus-related protective measures.Methods696 Finnish men and women aged over 77 answered a mailed questionnaire on their CHL, sources of information and perceptions of the restrictiveness of the recommended protective measures. The association of CHL with perceived restrictiveness was studied using multinomial logistic regression analysis.ResultsTelevision and newspapers were the most frequently reported sources of information. Reporting high confidence in the ability to assess how one’s behavior influences coronavirus infection risk was associated with higher odds of perceiving the protective measures to be highly restrictive, when controlling for age, gender, and difficulty in using digital devices (OR 3.21, 95% CI 1.09, 9.46).DiscussionParticipants who reported being highly confident about their ability to appraise the influence of their behavior on their susceptibility to coronavirus infection were more likely to perceive that the recommended protective measures had restricted their daily lives.ConclusionsHealth literacy plays a role in complying with recommended restrictions.

An Ontology-Driven Personalized Faceted Search for Exploring Knowledge Bases of Capsicum

Capsicum is a genus of flowering plants in the Solanaceae family in which the members are well known to have a high economic value. The Capsicum fruits, which are popularly known as peppers or chili, have been widely used by people worldwide. It serves as a spice and raw material for many products such as sauce, food coloring, and medicine. For many years, scientists have studied this plant to optimize its production. A tremendous amount of knowledge has been obtained and shared, as reflected in multiple knowledge-based systems, databases, or information systems. An approach to knowledge-sharing is through the adoption of a common ontology to eliminate knowledge understanding discrepancy. Unfortunately, most of the knowledge-sharing solutions are intended for scientists who are familiar with the subject. On the other hand, there are groups of potential users that could benefit from such systems but have minimal knowledge of the subject. For these non-expert users, finding relevant information from a less familiar knowledge base would be daunting. More than that, users have various degrees of understanding of the available content in the knowledge base. This understanding discrepancy raises a personalization problem. In this paper, we introduce a solution to overcome this challenge. First, we developed an ontology to facilitate knowledge-sharing about Capsicum to non-expert users. Second, we developed a personalized faceted search algorithm that provides multiple structured ways to explore the knowledge base. The algorithm addresses the personalization problem by identifying the degree of understanding about the subject from each user. In this way, non-expert users could explore a knowledge base of Capsicum efficiently. Our solution characterized users into four groups. As a result, our faceted search algorithm defines four types of matching mechanisms, including three ranking mechanisms as the core of our solution. In order to evaluate the proposed method, we measured the predictability degree of produced list of facets. Our findings indicated that the proposed matching mechanisms could tolerate various query types, and a high degree of predictability can be achieved by combining multiple ranking mechanisms. Furthermore, it demonstrates that our approach has a high potential contribution to biodiversity science in general, where many knowledge-based systems have been developed with limited access to users outside of the domain.

556-P: Codesigning a Diabetes Online Community Intervention for Adults with Type 1 and Type 2 Diabetes

Engagement in Diabetes Online Communities (DOCs) and diabetes online resources have proven benefits, including improved psychosocial, behavioral and clinical outcomes. However, patients report that finding credible and relevant information can be daunting. The aim of this study was to co-design an intervention with people with diabetes (PWD) to train “Peer Connectors” to help adults with type 1 and type 2 diabetes navigate DOCs and diabetes online resources to improve social support. A community advisory board (CAB) of 11 diverse (race, ethnicity, age, diabetes type, diabetes duration) PWD who were active in a variety of DOCs convened over four 2-hour meetings to discuss and prioritize intervention components and outcome measures. Field notes and audio recordings were analyzed to guide development of the D-COPES (Diabetes - Connecting Online Peers to Enhance Support) intervention. The CAB recommended three intervention components: 1) pairing participants to trained Peer Connectors based on matching characteristics/interests, (2) Peer Connectors delivering a small group intervention to orient participants to DOCs and online resources, and (3) Intervention content that includes tailoring to participants’ individual needs and how to identify misinformation. Recommended outcome measures focused on psychosocial (diabetes distress, empowerment), behavioral (self-efficacy, self-care), and clinical outcomes (A1C as secondary outcome), as well as usage of DOCs and online resources. The co-design process centered the D-COPES intervention on avoidance of misinformation and provided strategies to expand the benefits of DOCs to PWD who might not otherwise have the knowledge and skills to engage most effectively. Co-design also served as a form of social validation, ensuring the intervention itself would be of interest and socially relevant to PWD. The D-COPES intervention will be iteratively piloted with 12 participants over 12 weeks. Disclosure M. L. Litchman: Research Support; Self; Abbott Diabetes. T. Oser: Advisory Panel; Self; Cecelia Health, Dexcom, Inc., Advisory Panel; Spouse/Partner; Cecelia Health, Dexcom, Inc. C. Shockley: None. E. Grigorian: None. H. R. Walker: None. E. Wilson: None. A. Thompson: None. J. E. Blanchette: Board Member; Self; JDRF, Consultant; Self; Insulet Corporation, Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care, Research Support; Self; Association of Diabetes Care and Education Specialists. C. Rice: None. M. E. Hilliard: None. Funding Dick and Timmy Burton Foundation

Open Source Information’s Blind Spot

Abstract Digital open source information has been heralded for its democratizing potential, insofar as it allows access to a much broader range of sources and voices than would normally be consulted through traditional methods of information gathering for international criminal investigations. It also helps to overcome some of the physical access barriers that are commonplace in international criminal investigations. At a time when the use of digital open source information is becoming more widespread, this article warns of the cognitive and technical biases that can impact upon two key stages of an investigation: finding relevant information and analysing that information. At the information-gathering stage, there are particular crimes, regions and groups of people whose experiences are more likely to be overlooked or hidden in digital open source investigations. When it comes to analysing digital open source information, there is a danger that cognitive and technical biases may influence which information is deemed most relevant and useful to an international criminal investigation, and how that information is interpreted. This article proposes some steps that can be taken to mitigate these risks.

Assessing pre-service physics teachers’ competencies in designing photo-electric effect experiment using PhET simulation

The advancement of learning technology requires that pre-service physics teachers should have adequate skills to integrate technology in the teaching and learning process. This study aimed to investigate the competencies of prospective physics teacher of Jambi University in designing the photo-electric effect experiment. This study used a mixed method approach with exploratory models. Ninety physics education students of Jambi university, having taken modern physics subject, were participated. Data were obtained from the students′ work of designing photo-electric effect experiment using PhET simulation. The students were asked to work in group, but the final report was done individually. Data analysis were done based on indicators of competencies to design a virtual lab activity. The indicators consisted of abilities to declare the objectives of experiment, compile the theoretical basis, and set up the procedure. The findings showed that the average ability of the prospective physics teacher in designing photo-electric experiment using PhET simulation was in the low category. Based on interviews, it was due to aspects of unfamiliarity with PhET simulation, technical problems related java player installation, insufficient of prior knowledge, and lack of skills in finding relevant information.

VizCommender: Computing Text-Based Similarity in Visualization Repositories for Content-Based Recommendations

Cloud-based visualization services have made visual analytics accessible to a much wider audience than ever before. Systems such as Tableau have started to amass increasingly large repositories of analytical knowledge in the form of interactive visualization workbooks. When shared, these collections can form a visual analytic knowledge base. However, as the size of a collection increases, so does the difficulty in finding relevant information. Content-based recommendation (CBR) systems could help analysts in finding and managing workbooks relevant to their interests. Toward this goal, we focus on text-based content that is representative of the subject matter of visualizations rather than the visual encodings and style. We discuss the challenges associated with creating a CBR based on visualization specifications and explore more concretely how to implement the relevance measures required using Tableau workbook specifications as the source of content data. We also demonstrate what information can be extracted from these visualization specifications and how various natural language processing techniques can be used to compute similarity between workbooks as one way to measure relevance. We report on a crowd-sourced user study to determine if our similarity measure mimics human judgement. Finally, we choose latent Dirichlet allocation (LDA) as a specific model and instantiate it in a proof-of-concept recommender tool to demonstrate the basic function of our similarity measure.

General Learning Equilibrium Optimizer: A New Feature Selection Method for Biological Data Classification

ABSTRACT Finding relevant information from biological data is a critical issue for the study of disease diagnosis, especially when an enormous number of biological features are involved. Intentionally, the feature selection can be an imperative preprocessing step before the classification stage. Equilibrium optimizer (EO) is a recently established metaheuristic algorithm inspired by the principle of dynamic source and sink models when measuring the equilibrium states. In this research, a new variant of EO called general learning equilibrium optimizer (GLEO) is proposed as a wrapper feature selection method. This approach adopts a general learning strategy to help the particles to evade the local areas and improve the capability of finding promising regions. The proposed GLEO aims to identify a subset of informative biological features among a large number of attributes. The performance of the GLEO algorithm is validated on 16 biological datasets, where nine of them represent high dimensionality with a smaller number of instances. The results obtained show the excellent performance of GLEO in terms of fitness value, accuracy, and feature size in comparison with other metaheuristic algorithms.

FUNGSI KADERISASI DALAM MENINGKATAN KUALITAS KEPEMIMPINAN

Tujuan dari penelitian ini untuk mengetahui Fungsi kaderisasi dalam meningkatkan kualitas kepemimpinan. Pada Penelitian ini menggunakan metode studi pustaka (library reseach) dengan mengumpulkan sejumlah buku-buku, majalah, jurnal, lifet yang berkenaan dengan masalah dan tujuan penelitian. Pengumpulan data dengan hasil penelitian terdahulu yang menjadi pendukung data pada tema penelitian terkait kaderisasi kepemimpinan dan kualitas kepemimpinan dengan proses penelitian dimulai dengan tahapan mengidentifikasi, menemukan informasi yang relevan, menganalisis hasil temuan, dan kemudian mengembangkan dan mengekspresikannya menjadi temuan baru berkaitan dengan fungsi kaderisasi dalam miningkatkan kualitas kepemimpinan. Hasil Penelitian ini ditemukan bahwa, 1) Kaderisasi Informal, 2) Kaderisai Formal. Pemimpin yang baik bukan di lihat dari seberapa banyak pengikutnya, dan seberapa lama ia memimpin, tapi terlihat dari seberapa banyak ia bisa menciptakan pemimpin-pemimpin baru. Kepemimpinan mengacu pada suatu proses untuk menggerakkan sekumpulan manusia menuju ke suatu tujuan yang telah ditetapkan dengan mendorong mereka bertindak dengan cara tidak memaksa. Dengan demikian, dapat dikatakan bahwa kepemimpinan adalah suatu peranan dan juga merupakan suatu proses untuk memengaruhi orang lain. Sedangkan pemimpin adalah anggota dari suatu perkumpulan yang diberi kedudukan tertentu dan diharapkan dapat bertindak sesuai dengan kedudukannya. Seorang pemimpin adalah seseorang dalam suatu perkumpulan yang diharapkan mampumenggunakan pengaruhnya dalam mewujudkan dan mencapai tujuan kelompok yang disertai dengan penuh kejujuran. Pemimpin yang jujur ialah seorang yang memimpin dan bukan seorang yang menggunakan kedudukan untuk memimpin.

Integration PBL with RMS: Improving problem solving skills on environmental education

The environmental education course currently does not integrate problem-solving problem skills. The purpose of this study was analyzing the results of applying integration on problem-based learning with the RMS (reading, mind mapping, and sharing) learning model. The research method was a quasi-experimental with pre-test-post-test control group design. The study was conducted on 56 students who took an environmental education course in Natural Science Education Universitas Tidar. Data analysis used an Anacova test with a pretest as its covariate. The study results stated that 1) developed learning model integrates PBL with RMS learning model consisting of identifying problems, finding relevant information about problems through reading activities, analyzing problem: group discussion through mind mapping, providing solutions, and sharing results of mind mapping. 2) The integration of PBL with the RMS learning model indicated by an average score of post-test in the integration of PBL with the RMS learning model class of 68.46, and the traditional class of 48.92. 3) the learning process that occurs in the integration of PBL with the RMS learning model class shows that learning is run well, which is indicated by students' average evaluation score of the lecturer learning process. The integration of PBL and RMS model can be utilized by teachers and lecturers in Biology learning to have thinking skills and solve daily problems.

ANDDigest: a new web-based module of ANDSystem for the search of knowledge in the scientific literature

BackgroundThe rapid growth of scientific literature has rendered the task of finding relevant information one of the critical problems in almost any research. Search engines, like Google Scholar, Web of Knowledge, PubMed, Scopus, and others, are highly effective in document search; however, they do not allow knowledge extraction. In contrast to the search engines, text-mining systems provide extraction of knowledge with representations in the form of semantic networks. Of particular interest are tools performing a full cycle of knowledge management and engineering, including automated retrieval, integration, and representation of knowledge in the form of semantic networks, their visualization, and analysis. STRING, Pathway Studio, MetaCore, and others are well-known examples of such products. Previously, we developed the Associative Network Discovery System (ANDSystem), which also implements such a cycle. However, the drawback of these systems is dependence on the employed ontologies describing the subject area, which limits their functionality in searching information based on user-specified queries.ResultsThe ANDDigest system is a new web-based module of the ANDSystem tool, permitting searching within PubMed by using dictionaries from the ANDSystem tool and sets of user-defined keywords. ANDDigest allows performing the search based on complex queries simultaneously, taking into account many types of objects from the ANDSystem’s ontology. The system has a user-friendly interface, providing sorting, visualization, and filtering of the found information, including mapping of mentioned objects in text, linking to external databases, sorting of data by publication date, citations number, journal H-indices, etc. The system provides data on trends for identified entities based on dynamics of interest according to the frequency of their mentions in PubMed by years.ConclusionsThe main feature of ANDDigest is its functionality, serving as a specialized search for information about multiple associative relationships of objects from the ANDSystem’s ontology vocabularies, taking into account user-specified keywords. The tool can be applied to the interpretation of experimental genetics data, the search for associations between molecular genetics objects, and the preparation of scientific and analytical reviews. It is presently available at https://anddigest.sysbio.ru/.

Comparison of multi-response estimation methods

Prediction performance does not always reflect the estimation behaviour of a method. High error in estimation may necessarily not result in high prediction error, but can lead to an unreliable prediction if test data lie in a slightly different subspace than the training data. In addition, high estimation error often leads to unstable estimates, and consequently, the estimated effect of predictors on the response can not have a valid interpretation. Many research fields show more interest in the effect of predictor variables than actual prediction performance. This study compares some newly-developed (envelope) and well-established (PCR, PLS) estimation methods using simulated data with specifically designed properties such as Multicollinearity in the predictor variables, the correlation between multiple responses and the position of principal components corresponding to predictors that are relevant for the response. This study aims to give some insights into these methods and help the researchers to understand and use them for further study. Here we have, not surprisingly, found that no single method is superior to others, but each has its strength for some specific nature of data. In addition, the newly developed envelope method has shown impressive results in finding relevant information from data using significantly fewer components than the other methods.

ICT Infrastructure and Access to Online Services: Determining the Factors Affecting Faculty Satisfaction with University-Subscribed Resources

This paper examines the current status of IT facilities, access to online resources in the universities and the level of faculty satisfaction with university subscribed e-resources in Bangladesh. It employed two structured questionnaires for collecting data. The first questionnaire was sent to the library heads to obtain data about the current IT facilities, access to the online resources and the constraints faced by them in accessing e-resources. The second questionnaire was distributed to faculty member at public and private universities to assess their satisfaction and the difficulties that they encountered while accessing university’s online resources. Descriptive statistics were obtained with regard to university IT facilities, access to digital resources and the difficulties faced by the university libraries. Non-parametric statistical tests, such as Mann–Whitney and Kruskal–Wallis were carried out to identify the significant differences between and among faculty groups. Finally, an ordinal regression model was used to analyze the effects of demographic variables and computer experience level on faculty satisfaction. The library survey found that large university libraries had adequate IT facilities but the majority of the library heads stated they had problems such as inadequate financial support and lack of trained manpower. On the other hand, the faculty survey revealed that faculty members were not satisfied with the current level of e-resources that were subscribed by the libraries. Faculty members had difficulties in finding relevant information, access to e-resources from home and limited number of titles. There were no significant differences in the level of faculty satisfaction in terms of gender and designation but significant differences were found in case of university type. Few significant differences were found in terms of faculty age and teaching experience. However, significant differences were found in faculty satisfaction with regard to computer proficiency levels for several variables. The results of ordinal regression also showed university type and computer proficiency level do affect faculty satisfaction with university e-resources. This current study is significant as universities in Bangladesh are provided with better ICT facilities with access to new online resources and services. The paper proposes ways of enhancing access to e-resources and recommends appropriate corrective or regulatory measures to be taken.

Triggers and strategies related to the collaborative information-seeking behaviour of researchers in ResearchGate

PurposeThe purpose of this paper is to identify the triggers, strategies and outcomes of collaborative information-seeking behaviours of researchers on the ResearchGate social networking site.Design/methodology/approachData were collected from the population of researchers who use ResearchGate. The sample was limited to the Ph.D. students and assistant professors in the library and information science domain. Qualitative interviews were used for data collection.FindingsBased on the findings of the study, informal communications and complex information needs lead to a decision to use collaborative information-seeking behaviour. Also, easy access to sources of information and finding relevant information were the major positive factors contributing to collaborative information-seeking behaviour of the ResearchGate users. Users moved from collaborative Q&A strategies to sharing information, synthesising information and networking strategies based on their needs. Analysis of information-seeking behaviour showed that ResearchGate users bridged the information gap by internalizing new knowledge, making collaborative decisions and increasing their work's visibility.Originality/valueAs one of the initial studies on the collaborative information-seeking behaviour of ResearchGate users, this study provides a holistic picture of different triggers that affect researchers' information-seeking on ResearchGate.

Применение мобильных приложений при решении проблем региональной администрации или проблем малого бизнеса

The problem of finding relevant information and news for any field of activity is always relevant. Web-sitesbecome obsolete both structurally and informationally, more and more often users have to look for information on disparate resources, and as a business tool websites are no longer a quick and easy to im-plement solution. This paper is devoted tothe consideration of the possibility of using mobile applications, together or instead of classic sites, to solve regional problems for administrations of small cities and small businesses in the regions.

Studying health-related internet and mobile device use using web logs and smartphone records.

Many people use the internet to seek information that will help them understand their body and their health. Motivations for such behaviors are numerous. For example, users may wish to figure out a medical condition by searching for symptoms they experience. Similarly, they may seek more information on how to treat conditions they have been diagnosed with or seek resources on how to live a healthy life. With the ubiquitous availability of the internet, searching and finding relevant information is easier than ever before and a widespread phenomenon. To understand how people use the internet for health-related information, we use data from a sample of 1,959 internet users. A unique combination of data containing four months of users’ browsing histories and mobile application use on computers and mobile devices allows us to study which health websites they visited, what information they searched for and which health applications they used. Survey data inform us about users’ socio-demographic background, medical conditions and other health-related behaviors. Results show that women, young users, users with a university education and nonsmokers are most likely to use the internet and mobile applications for health-related purposes. On search engines, internet users most frequently search for pharmacies, symptoms of medical conditions and pain. Moreover, users seem most interested in information on how to live a healthy life, alternative medicine, mental health and women’s health. With this study, we extend the field’s understanding of who seeks and consumes health information online, what users look for as well as how individuals use mobile applications to monitor their health. Moreover, we contribute to methodological research by exploring new sources of data for understanding humans, their preferences and behaviors.