Information Retrieval Tools Research Articles

Automatic extraction of semantic relations between medical entities: a rule based approach

BackgroundInformation extraction is a complex task which is necessary to develop high-precision information retrieval tools. In this paper, we present the platform MeTAE (Medical Texts Annotation and Exploration). MeTAE allows (i) to extract and annotate medical entities and relationships from medical texts and (ii) to explore semantically the produced RDF annotations.ResultsOur annotation approach relies on linguistic patterns and domain knowledge and consists in two steps: (i) recognition of medical entities and (ii) identification of the correct semantic relation between each pair of entities. The first step is achieved by an enhanced use of MetaMap which improves the precision obtained by MetaMap by 19.59% in our evaluation. The second step relies on linguistic patterns which are built semi-automatically from a corpus selected according to semantic criteria. We evaluate our system’s ability to identify medical entities of 16 types. We also evaluate the extraction of treatment relations between a treatment (e.g. medication) and a problem (e.g. disease): we obtain 75.72% precision and 60.46% recall.ConclusionsAccording to our experiments, using an external sentence segmenter and noun phrase chunker may improve the precision of MetaMap-based medical entity recognition. Our pattern-based relation extraction method obtains good precision and recall w.r.t related works. A more precise comparison with related approaches remains difficult however given the differences in corpora and in the exact nature of the extracted relations. The selection of MEDLINE articles through queries related to known drug-disease pairs enabled us to obtain a more focused corpus of relevant examples of treatment relations than a more general MEDLINE query.

Języki informacyjne: między tradycją a nadzieją na cyfrową przyszłość

Przedstawiono propozycje zmian, jakie powinny nastąpić w językach informacyjnych (językach informacyjno-wyszukiwawczych, JIW), by jeszcze przez jakiś czas mo^y być narzędziem organizacji i wyszukiwania informacji. Rozważania są usytuowane w szerszym kontekście zjawisk, które kształtują obecnie środowisko informacyjno-wyszu- kiwawcze i oddziałują na JIW, a do których należą: ilość informacji będącej potencjalnym przedmiotem wyszukiwania oraz nowe obiekty informacyjne; zmiany w użjńtkownikach informacji, czyli w nas samych; tempo zmian; bezwzględna dominacja sieci. Wśród wniosków najważniejsze to: konieczność integracji zasobów informacji (przede wszystkim w Sieci); zmiana sposobu prezentacji słowników JIW (wizualizacje) z perspektjrwą przejścia w kierunku np. map wiedzy; integracja wyszukiwania metadanowego z przeszukiwaniem pełnych dokumentów.

A citation-based approach to automatic topical indexing of scientific literature

Topical indexing of documents with keyphrases is a common method used for revealing the subject of scientific and research documents to both human readers and information retrieval tools, such as search engines. However, scientific documents that are manually indexed with keyphrases are still in the minority. This article describes a new unsupervised method for automatic keyphrase extraction from scientific documents which yields a performance on a par with human indexers. The method is based on identifying references cited in the document to be indexed and, using the keyphrases assigned to those references, for generating a set of high-likelihood keyphrases for the document. We have evaluated the performance of the proposed method by using it to automatically index a third-party testset of research documents. Reported experimental results show that the performance of our method, measured in terms of consistency with human indexers, is competitive with that achieved by state-of-the-art supervised methods.

Convex non-negative matrix factorization for massive datasets

Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix into two non-negative matrix factors that contain basis elements and linear coefficients, respectively. Often, the columns of the first resulting factor are interpreted as “cluster centroids” of the input data, and the columns of the second factor are understood to contain cluster membership indicators. When analyzing data such as collections of gene expressions, documents, or images, it is often beneficial to ensure that the resulting cluster centroids are meaningful, for instance, by restricting them to be convex combinations of data points. However, known approaches to convex-NMF suffer from high computational costs and therefore hardly apply to large-scale data analysis problems. This paper presents a new framework for convex-NMF that allows for an efficient factorization of data matrices of millions of data points. Triggered by the simple observation that each data point can be expressed as a convex combination of vertices of the data convex hull, we require the basic factors to be vertices of the data convex hull. The benefits of convex-hull NMF are twofold. First, for a growing number of data points the expected size of the convex hull, i.e. the number of its vertices, grows much slower than the dataset. Second, distance preserving low-dimensional embeddings allow us to efficiently sample the convex hull and hence to quickly determine candidate vertices. Our extensive experimental evaluation on large datasets shows that convex-hull NMF compares favorably to convex-NMF in terms of both speed and reconstruction quality. We demonstrate that our method can easily be applied to large-scale, real-world datasets, in our case consisting of 750,000 DBLP entries, 4,000,000 digital images, and 150,000,000 votes on World of Warcraft ®guilds, respectively.

The Research about Intelligent Search Engine and in Digital Library Personalization Services

This article describes the working principle of search engine and classification, analyze the characteristics of intelligent search engine, according to the characteristics set up a work flow chart of the intelligent search engine, finally made how to apply intelligent search engine to digital library personalization services. With the emergence and development of the Internet search engine developed from the traditional to the intelligent search engine, as a new generation of information retrieval tools, intelligent search engine, relying on its own merits, is more and more applications to different fields..Web site survey showed that 75% of visits come from search engine referrals. How to effectively apply intelligent search engine to digital library, to build a digital library with our characteristics is a problem we face.

Retrieval of Web Documents Using a Fuzzy Hierarchical Clustering

ABSTRACT The World Wide Web has huge amount of information that is retrieved using information retrieval tool like Search Engine. Page repository of Search Engine contains the web documents downloaded by the crawler. This repository contains variety of web documents from different domains. In this paper, a technique called “Retrieval of Web documents using a fuzzy hierarchical clustering” is being proposed that creates the clusters of web documents using fuzzy hierarchical clustering. Keywords Search Engine, Web documents, Fuzzy Hierarchical Clustering Indexer 1. Introduction WWW [01, 02 and 04] is a huge repository of information consisting of hyperlinked documents spread over the internet. The size of the web as on February 2010 stands at around 35 million pages. For a user, it is practically impossible to search through this extremely large database for the information needed by him. Hence the need for Search Engine (see fig. 1) arises. The search engine uses crawlers to gather information and stores it in database maintained at search engine side. For a given user's query the search engine searches in the local database and very quickly displays the results. The huge amount of information [05] is retrieved using data mining tools. Classification, Clustering and Association tools etc. are used for data mining technique. Clustering plays a key role in searching for structures in data. As the number of available documents nowadays is large, hierarchical approaches are better suited because they permit categories to be defined at different pensiveness work about levels. The problem of clustering in finite set of data is to find several cluster centers that can properly characterize relevant classes of finite set of data such that degree of association is strong for data within blocks of the partition and weak for data in different blocks. When the weakness of a crisp partition of finite set of data is replaced with a fuzzy partition, this area is known as fuzzy clustering. Fuzzy clustering is a relevant technique for information retrieval. As a document might be relevant to multiple queries, this document should be given in the corresponding response sets, otherwise, the users would not be aware of it. Fuzzy clustering seems a natural technique for document categorization. There are two basic methods of fuzzy clustering, one which is based on fuzzy c-partitions, is called a fuzzy c-means clustering method and the other, based on the fuzzy equivalence relations, is called a fuzzy equivalence clustering method.

A five-year study of on-campus Internet use by undergraduate biomedical students

This paper reports on a five-year study (2005–2009) of biomedical students’ on-campus use of the Internet. Internet usage logs were used to investigate students’ sessional use of key websites and technologies. The most frequented sites and technologies included the university’s learning management system, Google, email and Facebook. Email was the primary method of electronic communication. However, its use declined over time, with a steep drop in use during 2006 and 2007 appearing to correspond with the rapid uptake of the social networking site Facebook. Both Google and Wikipedia gained in popularity over time while the use of other key information sources, including the library and biomedical portals, remained low throughout the study. With the notable exception of Facebook, most ‘Web 2.0’ technologies attracted little use. The ‘Net Generation’ students involved in this study were heavy users of generalist information retrieval tools and key online university services, and prefered to use externally hosted tools for online communication. These and other findings have important implications for the selection and provision of services by universities.

Concept-based query expansion for retrieving gene related publications from MEDLINE

BackgroundAdvances in biotechnology and in high-throughput methods for gene analysis have contributed to an exponential increase in the number of scientific publications in these fields of study. While much of the data and results described in these articles are entered and annotated in the various existing biomedical databases, the scientific literature is still the major source of information. There is, therefore, a growing need for text mining and information retrieval tools to help researchers find the relevant articles for their study. To tackle this, several tools have been proposed to provide alternative solutions for specific user requests.ResultsThis paper presents QuExT, a new PubMed-based document retrieval and prioritization tool that, from a given list of genes, searches for the most relevant results from the literature. QuExT follows a concept-oriented query expansion methodology to find documents containing concepts related to the genes in the user input, such as protein and pathway names. The retrieved documents are ranked according to user-definable weights assigned to each concept class. By changing these weights, users can modify the ranking of the results in order to focus on documents dealing with a specific concept. The method's performance was evaluated using data from the 2004 TREC genomics track, producing a mean average precision of 0.425, with an average of 4.8 and 31.3 relevant documents within the top 10 and 100 retrieved abstracts, respectively.ConclusionsQuExT implements a concept-based query expansion scheme that leverages gene-related information available on a variety of biological resources. The main advantage of the system is to give the user control over the ranking of the results by means of a simple weighting scheme. Using this approach, researchers can effortlessly explore the literature regarding a group of genes and focus on the different aspects relating to these genes.

Markup in Engineering Design: A Discourse

Today’s engineering companies are facing unprecedented competition in a global market place. There is now a knowledge intensive shift towards whole product lifecycle support, and collaborative environments. It has become particularly important to capture information, knowledge and experiences about previous design and following stages during their product lifecycle, so as to retrieve and reuse such information in new and follow-on designs activities. Recently, with the rapid development and adoption of digital technologies, annotation and markup are becoming important tools for information communication, retrieval and management. Such techniques are being increasingly applied to an array of applications and different digital items, such as text documents, 2D images and 3D models. This paper presents a state-of-the-art review of recent research in markup for engineering design, including a number of core markup languages and main markup strategies. Their applications and future utilization in engineering design, including multi-viewpoint of product models, capture of information and rationale across the whole product lifecycle, integration of engineering design processes, and engineering document management, are comprehensively discussed.

Analysis of Meta-Search Engines using the Meta-Meta-Search tool SSIR

information retrieval tools like Search Engines, Web Directories and deep-web search portals exist. Meta-search engines (MSE) developed over the past years claim to automatically and simultaneously search many other such information retrieval tools and improvise the fused results. This paper acquaints SSIR (http://www.ssir.in) a tier-three Meta- Search Engine or a Meta-meta search tool. Upon receiving a query, SSIR passes the modified query to various Meta-Search Engines in parallel, collects and processes the results and passes it to the user like any other Meta-Search Engine. Currently it is hosted as a live prototype and various improvements are being added. Apart from being a public software product used for internet searching, it is being used as a tool for analysis of overlaps and uniqueness among search results of various MSEs. The study also analyses the percentage of contribution in the top results of popular search engines Google, Yahoo and Windows-Live in the top results covered by individual MSEs and by SSIR.

Information-Retrieval Tool for Math Expressions as Infrastructure of Training Engineers via E-Learning

In this study, it's our objective to develop an information-retrieval tool for mathematical expressions to enhance usability of contents including math. The authors believe such infrastructure is essential for training engineers via e-Learning, especially in the field of control engineering where learners are required to manipulate equations and functions. Our target is math expressions written by Presentation MathML (Mathematical Markup Language), which was developed for describing math on the web. The results of pilot experiments are also shown.

The Hyperbolic Brower as a Tool for Information Visualization, Discovery, and Retrieval on the Web and Enterprise Intranets

The Hyperbolic Brower as a Tool for Information Visualization, Discovery, and Retrieval on the Web and Enterprise Intranets

The Hyperbolic Brower as a Tool for Information Visualization, Discovery, and Retrieval on the Web and Enterprise Intranets

Knowledge workers frequently need to locate task-relevant information quickly and efficiently through the Internet or their enterprise intranets. The ability to visualize how information is structured and organized is often a key to timely and efficient information discovery and retrieval. The traditional interface used for browsing Web sites has been a hierarchical, tree-like presentation, such as the Windows Explorer file/folder browser. From a user interface design standpoint, an attractive alternative to this type of browser is the hyperbolic browser, which is a focus + context technique for visualizing and browsing large amounts of hierarchical inter-related information. A hyperbolic view display efficiently represents hierarchical and associative information in a static or dynamic visual format using a relatively small display space. This paper discusses the characteristics of the hyperbolic browser, provides a real-life use case scenario to illustrate its application, and suggests avenues for future research and development.

Introduction to Search 2009

Search is like the blind men and the elephant. The story goes that four blind men approached an elephant. By touching the hide, trunk, tail and legs each thought of the elephant as an entirely different animal. From the hide we can conclude that search is a contextual process where searchers must aimlessly feel around until they either accidentally find what they want or give up. From the trunk we can conclude that search should be like a fire hose where we flood the searchers with content, overwhelming them. The tail? From this perspective search is seen as the infamous “long tail” wherein searchers are fed minuscule tidbits of esoterica, leaving them curious, but famished.And those feeling the legs would conclude that we should stomp the content into submission, pulverizing until it is unrecognizable.

Challenges for automatically extracting molecular interactions from full-text articles

BackgroundThe increasing availability of full-text biomedical articles will allow more biomedical knowledge to be extracted automatically with greater reliability. However, most Information Retrieval (IR) and Extraction (IE) tools currently process only abstracts. The lack of corpora has limited the development of tools that are capable of exploiting the knowledge in full-text articles. As a result, there has been little investigation into the advantages of full-text document structure, and the challenges developers will face in processing full-text articles.ResultsWe manually annotated passages from full-text articles that describe interactions summarised in a Molecular Interaction Map (MIM). Our corpus tracks the process of identifying facts to form the MIM summaries and captures any factual dependencies that must be resolved to extract the fact completely. For example, a fact in the results section may require a synonym defined in the introduction. The passages are also annotated with negated and coreference expressions that must be resolved.We describe the guidelines for identifying relevant passages and possible dependencies. The corpus includes 2162 sentences from 78 full-text articles. Our corpus analysis demonstrates the necessity of full-text processing; identifies the article sections where interactions are most commonly stated; and quantifies the proportion of interaction statements requiring coherent dependencies. Further, it allows us to report on the relative importance of identifying synonyms and resolving negated expressions. We also experiment with an oracle sentence retrieval system using the corpus as a gold-standard evaluation set.ConclusionWe introduce the MIM corpus, a unique resource that maps interaction facts in a MIM to annotated passages within full-text articles. It is an invaluable case study providing guidance to developers of biomedical IR and IE systems, and can be used as a gold-standard evaluation set for full-text IR tasks.

A community-curated consensual annotation that is continuously updated: the Bacillus subtilis centred wiki SubtiWiki

Bacillus subtilis is the model organism for Gram-positive bacteria, with a large amount of publications on all aspects of its biology. To facilitate genome annotation and the collection of comprehensive information on B. subtilis, we created SubtiWiki as a community-oriented annotation tool for information retrieval and continuous maintenance. The wiki is focused on the needs and requirements of scientists doing experimental work. This has implications for the design of the interface and for the layout of the individual pages. The pages can be accessed primarily by the gene designations. All pages have a similar flexible structure and provide links to related gene pages in SubtiWiki or to information in the World Wide Web. Each page gives comprehensive information on the gene, the encoded protein or RNA as well as information related to the current investigation of the gene/protein. The wiki has been seeded with information from key publications and from the most relevant general and B. subtilis-specific databases. We think that SubtiWiki might serve as an example for other scientific wikis that are devoted to the genes and proteins of one organism.Database URL: The wiki can be accessed at http://subtiwiki.uni-goettingen.de/

The selection of high-impact health informatics literature: a comparison of results between the content expert and the expert searcher

The Agency for Healthcare Research and Quality (AHRQ) National Resource Center for Health Information Technology (NRC) created the Health IT Bibliography that contains peer-reviewed articles in eleven different health informatics categories. To create the bibliography, informatics experts identified what they considered the seminal articles in each category. Using the same eleven categories, an expert searcher (librarian) compiled a list of the "best" health informatics articles using information seeking and retrieval tools. The two sets of articles were then compared using high citation counts as a measure of value. The expert searcher set (8,230) contained more than 3 times the citations to chosen articles compared to the content expert set (2,382). Of 60 articles, 27% of those articles (n = 16) were included in both sets. The frequently cited journals were similar for both sets, and one-third of the same authors were cited in both sets. While citation counts and the timeliness of the articles differed in the two sets, the same authors and same journals were frequently present in both sets. A best practice for locating high-quality articles may be collaboration between expert searchers and content experts.

GeneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research.

BackgroundBioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine.ResultsIn addressing the issue of bridging the existing gap between biomedical researchers and clinicians who work in the domain of cancer diagnosis, prognosis and treatment, we have developed and made accessible a common interactive framework. Our geneCBR system implements a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction for aiding diagnosis in cancer research. For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. For pathologists or oncologists, geneCBR diagnostic mode implements an effective and reliable system that can diagnose cancer subtypes based on the analysis of microarray data using a CBR architecture. For programmers, geneCBR programming mode includes an advanced edition module for run-time modification of previous coded techniques.ConclusiongeneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. The code is freely available under the GPL license and can be obtained at .

Information Literacy: More to Learn--and Teach!

Robert Phillips is Associate Dean of Libraries at A. Webb Roberts Library at Southwestern Baptist Theological Seminary, Fort Worth, Texas. The emphasis on information literacy has moved library instruction to a new level. before, we focused on the library as the repository of information, on the tools librarians had created to manage that repository, and on the librarians themselves with their accumulated training, experience, and knowledge of both the place and the tools. Yet without formal instruction, students learned that no longer are libraries the only source for information; that computer programmers can also create tools for information retrieval; and that librarians, though knowledgeable, are not always available when needed. librarians must counter this trend by saying, “Wait, we weren’t finished. There is still more to learn.”

Text mining for Swiss-Prot curation: A story of success and failure

AbstractA text mining group has been set up at the Swiss Institute of Bioinformatics, with objective to develop and adapt information retrieval and extraction tools to help Swiss-Prot curators in their daily annotation work. After over 7 year activities, this group has gathered a significant amount of experience about the need in text mining for biocuration.The first observation we made is that there is no “in-a-box” solution which can satisfy every needs. Each curator has his/her own strategy to find information from the literature and none of the existing information retrieval systems is able to compete with it, more for reason of habits than for reason of performance. Second observation: to be completely operative, an information retrieval system should be embedded in the annotation platform. For instance, it should be possible to copy/paste information, such as the article reference or some interesting sentences, directly in the database format. Most of the existing online programs are hardly adaptable for this task and their use usually results in additional editing efforts for the curators. From this observation, we can derive the fact that integrating text mining services is usually more costly than expected since wrappers and user interfaces need significant developments sometimes fairly user-specific.After noticing these problems in the design and use of a generic information retrieval system for the Swiss-Prot curators, we focused our effort on text mining applications for database update. The follow-up of the literature is essential in the process of database maintenance and there are needs for automatic information extraction tools on a large panel of topics. We developed several IE applications in the field of:- PTM information (phosphorylation, glycosylation, disulfide bridge)- Subcellular localization- Variant/mutation detection and characterization- New sequence with enzymatic activities- New characterization of enzymes.These tools are integrated into pipelines which follow PubMed daily outcomes and generate list of selected abstracts with highlights on the relevant sentences. These procedures are done independently of the usual annotation workflow, so that curators can mine these preselected data whenever they work on database entry updates.To conclude, we have identified big challenges in text mining services after discussion with the curators. One of them is the detection of novel information, especially those related to a new function or a new characterization of a protein or one of its close homologues. We are currently working on this task in the framework of the collaborative project “EAGL”. Another challenge is definitely the large-scale screening of newly published full-text papers to complement the often incomplete information in abstracts. This becomes more and more indispensable, not really for the annotation of widely studied “hot” proteins, but to find new data on uncharacterized ones. For instance, when no gene name has been attributed to a sequence, the only way to retrieve information is to use the orf names, which are never provided in abstracts.Finally, one should definitely stress that many of these information retrieval and extraction tasks could be greatly simplified with the requirement of metadata at the article submission time, such as an official HGNC gene name or a UniProt reference.