Organizing Search Results Research Articles

Natural language processing methods for knowledge management—Applying document clustering for fast search and grouping of engineering documents

Product development companies collect data in form of Engineering Change Requests for logged design issues, tests, and product iterations. These documents are rich in unstructured data (e.g. free text). Previous research affirms that product developers find that current IT systems lack capabilities to accurately retrieve relevant documents with unstructured data. In this research, we demonstrate a method using Natural Language Processing and document clustering algorithms to find structurally or contextually related documents from databases containing Engineering Change Request documents. The aim is to radically decrease the time needed to effectively search for related engineering documents, organize search results, and create labeled clusters from these documents by utilizing Natural Language Processing algorithms. A domain knowledge expert at the case company evaluated the results and confirmed that the algorithms we applied managed to find relevant document clusters given the queries tested.

EarthCube Data Discovery Studio: A gateway into geoscience data discovery and exploration with Jupyter notebooks

AbstractEarthCube Data Discovery Studio (DDStudio) is a crossdomain geoscience data discovery and exploration portal. It indexes over 1.65 million metadata records harvested from 40+ sources and utilizes a configurable metadata augmentation pipeline to enhance metadata content, using text analytics and an integrated geoscience ontology. Metadata enhancers add keywords with identifiers that map resources to science domains, geospatial features, measured variables, and other characteristics. The pipeline extracts spatial location and temporal references from metadata to generate structured spatial and temporal extents, maintaining provenance of each metadata enhancement, and allowing user validation. The semantically enhanced metadata records are accessible as standard ISO 19115/19139 XML documents via standard search interfaces. A search interface supports spatial, temporal, and text‐based search, as well as functionality for users to contribute, standardize, and update resource descriptions, and to organize search results into shareable collections. DDStudio bridges resource discovery and exploration by letting users launch Jupyter notebooks residing on several platforms for any discovered datasets or dataset collection. DDStudio demonstrates how linking search results from the catalog directly to software tools and environments reduces time to science in a series of examples from several geoscience domains. URL: datadiscoverystudio.org

A Concept-Based Approach for Generating Better Topics for Web Search Results

As the web is accessible to a vast population around the globe, web users today pose a large number of queries, with dynamic, vague and unclear intentions, using the web search tools, as a consequence of which organizing search results have become an all the more challenging task. Further, because of such web queries, it is difficult for web search tools to comprehend the exact user context, and thus they retrieve an extensive volume of results, a significant portion of which are unnecessary for the user. One of the answers to this problem is a strategy called search result clustering (SRC), which bunches the search results and presents them to users with many options for the query. In this work, we have proposed an approach that initially classifies the related topics and lays them out in the form of concepts, and then building search results clusters by designating each to the relevant topic and finally, providing relevant labels for these topics. We examine the effectiveness of our approach by measuring it against two most popular non-commercial methods in this field, specifically Lingo and STC, with two standard datasets, ODP and Ambient, and a newly developed dataset, Ex-Ambient, which is a rigorously extended version of the Ambient Dataset. We performed analysis on both qualitative and quantitative dimensions. We define a qualitative dimension as the expressiveness of the cluster label generated, while quantitative dimension regards the correctness of the document assigned to the cluster. The experimental results presented by the proposed method were encouraging in contrast with Lingo and STC for all the datasets and both the dimensions.

Maternal Hemoglobin Concentrations Across Pregnancy and Maternal and Child Health: A Systematic Review and Meta-analysis (P11-033-19)

ObjectivesMaternal anemia is a well-recognized global health problem; however, there remain questions on specific hemoglobin thresholds that predict health risk or protection for mother and child. Our objective was to conduct a systematic review and meta-analysis to examine the associations of maternal hemoglobin concentrations with a range of maternal and infant health outcomes, accounting for timing of measurement (preconception, first, second and third trimesters), etiology of anemia and cut-off category. MethodsOur search strategy identified 7,677 articles. Screening and article selection was conducted using Covidence systematic review software to organize search results from PubMed and Cochrane Review. The systematic review included 272 studies and the meta-analysis included 102 studies. ResultsLow maternal hemoglobin (< 110 g/L) was associated with poor birth outcomes (low birth weight, OR (95%CI): 1.43 (1.31-1.55); preterm birth, 1.35 (1.25-1.46); small-for-gestational age, 1.08 (1.00-1.18); stillbirth, 1.43 (1.05-1.95); perinatal mortality, 1.73 (1.32-2.26); and neonatal mortality, 1.49 (1.19-1.87); and adverse maternal outcomes (post-partum hemorrhage, 2.17 (1.51-3.10); preeclampsia, 1.84 (1.31-2.59); and blood-transfusion, 6.57 (3.59-12.00). High maternal hemoglobin (> 130 g/L) was associated with increased odds of small-for-gestational age, 1.22 (1.08-1.37); stillbirth, 1.88 (1.21-2.91); preeclampsia, 1.48 (1.10-2.01); and gestational diabetes, 2.02 (1.63-2.50). Relationships varied by timing of measurement and cut-off category; limited data were available on anemia etiology. There were insufficient data for other maternal outcomes and long-term child health outcomes. ConclusionsCurrent data are insufficient for determining if revisions to current hemoglobin cut-offs are required. Pooled high-quality individual-level data analyses as well as prospective cohort studies that measure hemoglobin throughout pregnancy would be valuable to inform the re-evaluation of hemoglobin cut-offs. Funding SourcesThis work was commissioned and financially supported by the Evidence and Programme Guidance Unit, Department of Nutrition for Health and Development of the World Health Organization (WHO), Geneva, Switzerland.

Multi-focus cluster labeling

Document collections resulting from searches in the biomedical literature, for instance, in PubMed, are often so large that some organization of the returned information is necessary. Clustering is an efficient tool for organizing search results. To help the user to decide how to continue the search for relevant documents, the content of each cluster can be characterized by a set of representative keywords or cluster labels. As different users may have different interests, it can be desirable with solutions that make it possible to produce labels from a selection of different topical categories. We therefore introduce the concept of multi-focus cluster labeling to give users the possibility to get an overview of the contents through labels from multiple viewpoints.The concept for multi-focus cluster labeling has been established and has been demonstrated on three different document collections. We illustrate that multi-focus visualizations can give an overview of clusters along axes that general labels are not able to convey. The approach is generic and should be applicable to any biomedical (or other) domain with any selection of foci where appropriate focus vocabularies can be established. A user evaluation also indicates that such a multi-focus concept is useful.

Organizing Search Results with a Reference Map.

We propose a method to highlight query hits in hierarchically clustered collections of interrelated items such as digital libraries or knowledge bases. The method is based on the idea that organizing search results similarly to their arrangement on a fixed reference map facilitates orientation and assessment by preserving a user's mental map. Here, the reference map is built from an MDS layout of the items in a Voronoi treemap representing their hierarchical clustering, and we use techniques from dynamic graph layout to align query results with the map. The approach is illustrated on an archive of newspaper articles.

Transitions in search tactics during the Web‐based search process

AbstractAlthough many studies have identified search tactics, few studies have explored tactic transitions. This study investigated the transitions of search tactics during the Web‐based search process. Bringing their own 60 search tasks, 31 participants, representing the general public with different demographic characteristics, participated in the study. Data collected from search logs and verbal protocols were analyzed by applying both qualitative and quantitative methods. The findings of this study show that participants exhibited some unique Web search tactics. They overwhelmingly employed accessing and evaluating tactics; they used fewer tactics related to modifying search statements, monitoring the search process, organizing search results, and learning system features. The contributing factors behind applying most and least frequently employed search tactics are in relation to users' efforts, trust in information retrieval (IR) systems, preference, experience, and knowledge as well as limitation of the system design. A matrix of search‐tactic transitions was created to show the probabilities of transitions from one tactic to another. By applying fifth‐order Markov chain, the results also presented the most common search strategies representing patterns of tactic transition occurring at the beginning, middle, and ending phases within one search session. The results of this study generated detailed and useful guidance for IR system design to support the most frequently applied tactics and transitions, to reduce unnecessary transitions, and support transitions at different phases.

A survey of Web clustering engines

Web clustering engines organize search results by topic, thus offering a complementary view to the flat-ranked list returned by conventional search engines. In this survey, we discuss the issues that must be addressed in the development of a Web clustering engine, including acquisition and preprocessing of search results, their clustering and visualization. Search results clustering, the core of the system, has specific requirements that cannot be addressed by classical clustering algorithms. We emphasize the role played by the quality of the cluster labels as opposed to optimizing only the clustering structure. We highlight the main characteristics of a number of existing Web clustering engines and also discuss how to evaluate their retrieval performance. Some directions for future research are finally presented.

The Usefulness of Dynamically Categorizing Search Results

The authors' goal was to determine whether dynamic categorization, a new technique for organizing search results, is more useful than the two existing organizational techniques: relevance ranking and clustering. They define a useful tool as one that helps users learn about the kinds of information that pertain to their query, find answers to their questions efficiently and easily, and feel satisfied with their search experience. Fifteen patients with breast cancer and their family members completed query-related tasks using all three tools. The authors measured the time it took the subjects to accomplish their tasks, the number of answers to the query that the subjects found in four minutes, and the number of new answers that they could recall at the end of the study. Subjects also completed a user-satisfaction questionnaire. The results showed that patients with breast cancer and their family members could find significantly (P: < 0.05) more answers in a fixed amount of time and were significantly (P: < 0.05) more satisfied with their search experience when they used the dynamic categorization tool than when they used either the cluster tool or the ranking tool. Subjects indicated that the dynamic categorization tool provided an organization of search results that was more clear, easy to use, accurate, precise, and helpful than those of the other tools. The experiments indicate that dynamic categorization is an effective and useful approach for organizing search results. Tools that use this technique will help patients and their families gain quick and easy access to important medical information.