TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 10: Text Mining

This class introduces basics of web mining and information retrieval including, for example, an introduction to the Vector Space Model and Text Mining. Guest Lecturer: Dr. Michael Granitzer Optional: Modeling the Internet and the Web: Probabilistic Methods and Algorithms, Pierre Baldi, Paolo Frasconi, Padhraic Smyth, Wiley, 2003 (Chapter 4, Text Analysis)

Nanoinformatics approaches for information extraction and text mining in nanomedical research texts

La nanotecnología es un área de investigación de reciente creación que trata con la manipulación y el control de la materia con dimensiones comprendidas entre 1 y 100 nanómetros. A escala nanométrica, los materiales exhiben fenómenos físicos, químicos y biológicos singulares, muy distintos a los que manifiestan a escala convencional. En medicina, los compuestos miniaturizados a nanoescala y los materiales nanoestructurados ofrecen una mayor eficacia con respecto a las formulaciones químicas tradicionales, así como una mejora en la focalización del medicamento hacia la diana terapéutica, revelando así nuevas propiedades diagnósticas y terapéuticas. A su vez, la complejidad de la información a nivel nano es mucho mayor que en los niveles biológicos convencionales (desde el nivel de población hasta el nivel de célula) y, por tanto, cualquier flujo de trabajo en nanomedicina requiere, de forma inherente, estrategias de gestión de información avanzadas. Desafortunadamente, la informática biomédica todavía no ha proporcionado el marco de trabajo que permita lidiar con estos retos de la información a nivel nano, ni ha adaptado sus métodos y herramientas a este nuevo campo de investigación. En este contexto, la nueva área de la nanoinformática pretende detectar y establecer los vínculos existentes entre la medicina, la nanotecnología y la informática, fomentando así la aplicación de métodos computacionales para resolver las cuestiones y problemas que surgen con la información en la amplia intersección entre la biomedicina y la nanotecnología. Las observaciones expuestas previamente determinan el contexto de esta tesis doctoral, la cual se centra en analizar el dominio de la nanomedicina en profundidad, así como en el desarrollo de estrategias y herramientas para establecer correspondencias entre las distintas disciplinas, fuentes de datos, recursos computacionales y técnicas orientadas a la extracción de información y la minería de textos, con el objetivo final de hacer uso de los datos nanomédicos disponibles. El autor analiza, a través de casos reales, alguna de las tareas de investigación en nanomedicina que requieren o que pueden beneficiarse del uso de métodos y herramientas nanoinformáticas, ilustrando de esta forma los inconvenientes y limitaciones actuales de los enfoques de informática biomédica a la hora de tratar con datos pertenecientes al dominio nanomédico. Se discuten tres escenarios diferentes como ejemplos de actividades que los investigadores realizan mientras llevan a cabo su investigación, comparando los contextos biomédico y nanomédico: i) búsqueda en la Web de fuentes de datos y recursos computacionales que den soporte a su investigación; ii) búsqueda en la literatura científica de resultados experimentales y publicaciones relacionadas con su investigación; iii) búsqueda en registros de ensayos clínicos de resultados clínicos relacionados con su investigación. El desarrollo de estas actividades requiere el uso de herramientas y servicios informáticos, como exploradores Web, bases de datos de referencias bibliográficas indexando la literatura biomédica y registros online de ensayos clínicos, respectivamente. Para cada escenario, este documento proporciona un análisis detallado de los posibles obstáculos que pueden dificultar el desarrollo y el resultado de las diferentes tareas de investigación en cada uno de los dos campos citados (biomedicina y nanomedicina), poniendo especial énfasis en los retos existentes en la investigación nanomédica, campo en el que se han detectado las mayores dificultades. El autor ilustra cómo la aplicación de metodologías provenientes de la informática biomédica a estos escenarios resulta efectiva en el dominio biomédico, mientras que dichas metodologías presentan serias limitaciones cuando son aplicadas al contexto nanomédico. Para abordar dichas limitaciones, el autor propone un enfoque nanoinformático, original, diseñado específicamente para tratar con las características especiales que la información presenta a nivel nano. El enfoque consiste en un análisis en profundidad de la literatura científica y de los registros de ensayos clínicos disponibles para extraer información relevante sobre experimentos y resultados en nanomedicina —patrones textuales, vocabulario en común, descriptores de experimentos, parámetros de caracterización, etc.—, seguido del desarrollo de mecanismos para estructurar y analizar dicha información automáticamente. Este análisis concluye con la generación de un modelo de datos de referencia (gold standard) —un conjunto de datos de entrenamiento y de test anotados manualmente—, el cual ha sido aplicado a la clasificación de registros de ensayos clínicos, permitiendo distinguir automáticamente los estudios centrados en nanodrogas y nanodispositivos de aquellos enfocados a testear productos farmacéuticos tradicionales. El presente trabajo pretende proporcionar los métodos necesarios para organizar, depurar, filtrar y validar parte de los datos nanomédicos existentes en la actualidad a una escala adecuada para la toma de decisiones. Análisis similares para otras tareas de investigación en nanomedicina ayudarían a detectar qué recursos nanoinformáticos se requieren para cumplir los objetivos actuales en el área, así como a generar conjunto de datos de referencia, estructurados y densos en información, a partir de literatura y otros fuentes no estructuradas para poder aplicar nuevos algoritmos e inferir nueva información de valor para la investigación en nanomedicina. ABSTRACT Nanotechnology is a research area of recent development that deals with the manipulation and control of matter with dimensions ranging from 1 to 100 nanometers. At the nanoscale, materials exhibit singular physical, chemical and biological phenomena, very different from those manifested at the conventional scale. In medicine, nanosized compounds and nanostructured materials offer improved drug targeting and efficacy with respect to traditional formulations, and reveal novel diagnostic and therapeutic properties. Nevertheless, the complexity of information at the nano level is much higher than the complexity at the conventional biological levels (from populations to the cell). Thus, any nanomedical research workflow inherently demands advanced information management. Unfortunately, Biomedical Informatics (BMI) has not yet provided the necessary framework to deal with such information challenges, nor adapted its methods and tools to the new research field. In this context, the novel area of nanoinformatics aims to build new bridges between medicine, nanotechnology and informatics, allowing the application of computational methods to solve informational issues at the wide intersection between biomedicine and nanotechnology. The above observations determine the context of this doctoral dissertation, which is focused on analyzing the nanomedical domain in-depth, and developing nanoinformatics strategies and tools to map across disciplines, data sources, computational resources, and information extraction and text mining techniques, for leveraging available nanomedical data. The author analyzes, through real-life case studies, some research tasks in nanomedicine that would require or could benefit from the use of nanoinformatics methods and tools, illustrating present drawbacks and limitations of BMI approaches to deal with data belonging to the nanomedical domain. Three different scenarios, comparing both the biomedical and nanomedical contexts, are discussed as examples of activities that researchers would perform while conducting their research: i) searching over the Web for data sources and computational resources supporting their research; ii) searching the literature for experimental results and publications related to their research, and iii) searching clinical trial registries for clinical results related to their research. The development of these activities will depend on the use of informatics tools and services, such as web browsers, databases of citations and abstracts indexing the biomedical literature, and web-based clinical trial registries, respectively. For each scenario, this document provides a detailed analysis of the potential information barriers that could hamper the successful development of the different research tasks in both fields (biomedicine and nanomedicine), emphasizing the existing challenges for nanomedical research —where the major barriers have been found. The author illustrates how the application of BMI methodologies to these scenarios can be proven successful in the biomedical domain, whilst these methodologies present severe limitations when applied to the nanomedical context. To address such limitations, the author proposes an original nanoinformatics approach specifically designed to deal with the special characteristics of information at the nano level. This approach consists of an in-depth analysis of the scientific literature and available clinical trial registries to extract relevant information about experiments and results in nanomedicine —textual patterns, common vocabulary, experiment descriptors, characterization parameters, etc.—, followed by the development of mechanisms to automatically structure and analyze this information. This analysis resulted in the generation of a gold standard —a manually annotated training or reference set—, which was applied to the automatic classification of clinical trial summaries, distinguishing studies focused on nanodrugs and nanodevices from those aimed at testing traditional pharmaceuticals. The present work aims to provide the necessary methods for organizing, curating and validating existing nanomedical data on a scale suitable for decision-making. Similar analysis for different nanomedical research tasks would help to detect which nanoinformatics resources are required to meet current goals in the field, as well as to generate densely populated and machine-interpretable reference datasets from the literature and other unstructured sources for further testing novel algorithms and inferring new valuable information for nanomedicine.

Towards a unified framework for opinion retrieval, mining and summarization

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.

TEXT-MESS: Intelligent, Interactive and Multilingual Text Mining based on Human Language Technologies, TIN2006-15265-C06

The goal of the project is to analyze, experiment, and develop intelligent, interactive and multilingual Text Mining technologies, as a key element of the next generation of search engines, systems with the capacity to find "the need behind the query". This new generation will provide specialized services and interfaces according to the search domain and type of information needed. Moreover, it will integrate textual search (websites) and multimedia search (images, audio, video), it will be able to find and organize information, rather than generating ranked lists of websites.

Dynamic Social and Media Content Syndication for Second Screen

Social networking apps, sites and technologies offer a wide range of opportunities for businesses and developers to exploit the vast amount of information and user-generated content produced through social networking. In addition, the notion of second screen TV usage appears more influential than ever, with viewers continuously seeking further information and deeper engagement while watching their favourite movies or TV shows. In this work, the authors present SAM, an innovative platform that combines social media, content syndication and targets second screen usage to enhance media content provisioning, renovate the interaction with end-users and enrich their experience. SAM incorporates modern technologies and novel features in the areas of content management, dynamic social media, social mining, semantic annotation and multi-device representation to facilitate an advanced business environment for broadcasters, content and metadata providers, and editors to better exploit their assets and increase their revenues.

Meeting on Provisions in Licensing Incorporating new developments in daily licensing practice: Setting conditions for open access, patron driven access, and data & text mining

Following the workshop on new developments in daily licensing practice in November 2011, we brought together fourteen representatives from national consortia (from Denmark, Germany, Netherlands and the UK) and publishers (Elsevier, SAGE and Springer) met in Copenhagen on 9 March 2012 to discuss provisions in licences to accommodate new developments. The one day workshop aimed to: present background and ideas regarding the provisions KE Licensing Expert Group developed; introduce and explain the provisions the invited publishers currently use;ascertain agreement on the wording for long term preservation, continuous access and course packs; give insight and more clarity about the use of open access provisions in licences; discuss a roadmap for inclusion of the provisions in the publishers’ licences; result in report to disseminate the outcome of the meeting. Participants of the workshop were: United Kingdom: Lorraine Estelle (Jisc Collections) Denmark: Lotte Eivor Jørgensen (DEFF), Lone Madsen (Southern University of Denmark), Anne Sandfær (DEFF/Knowledge Exchange) Germany: Hildegard Schaeffler (Bavarian State Library), Markus Brammer (TIB) The Netherlands: Wilma Mossink (SURF), Nol Verhagen (University of Amsterdam), Marc Dupuis (SURF/Knowledge Exchange) Publishers: Alicia Wise (Elsevier), Yvonne Campfens (Springer), Bettina Goerner (Springer), Leo Walford (Sage) Knowledge Exchange: Keith Russell The main outcome of the workshop was that it would be valuable to have a standard set of clauses which could used in negotiations, this would make concluding licences a lot easier and more efficient. The comments on the model provisions the Licensing Expert group had drafted will be taken into account and the provisions will be reformulated. Data and text mining is a new development and demand for access to allow for this is growing. It would be easier if there was a simpler way to access materials so they could be more easily mined. However there are still outstanding questions on how authors of articles that have been mined can be properly attributed.

FLOW PROPERTIES AND TUBE FRICTION FACTOR OF MILK CREAM: INFLUENCE OF TEMPERATURE AND FAT CONTENT

The rheological behavior of milk cream was studied for different fat contents (0.10 to 0.31) and for a wide temperature range (2 and 87C) using a rotational rheometer. Newtonian behavior was observed, except for fat content between 0.20 and 0.31 and temperature between 2 and 33C, where viscoplastic behavior was remarkable. The rheological parameters (Newtonian viscosity, plastic viscosity and yield stress) and density were well correlated to temperature and fat content. Tube friction factor during flow of cream was experimentally obtained at various flow rates, temperatures and tube diameters (86 < Re < 2.3 x 104, 38 < Re(B) < 8.8 x 103, 1.1 x 103 < He < 6.7 x 103). The proposed correlations for density and rheological parameters were applied for the prediction of friction factor for laminar and turbulent flow of cream using well-known equations for Newtonian and viscoplastic flow. The good agreement between experimental and predicted values confirms the reliability of the proposed correlations for describing the flow behavior of cream. PRACTICAL APPLICATIONS This paper presents correlations for the calculation of density and rheological parameters (Newtonian viscosity, Bingham plastic viscosity and yield stress) of milk cream as functions of temperature (2-87C) and fat content (0.10-0.31). Because of the large temperature range, the proposed correlations are useful for process design and optimization in dairy processing. An example of practical application is presented in the text, where the correlations were applied for the prediction of friction factor for laminar and turbulent tube flow of cream using well-known equations for Newtonian and viscoplastic flow, which are summarized in the text. The comparison with experimental data obtained at various flow rates, temperatures and tube diameters showed a good agreement, which confirms the reliability of the proposed correlations.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Effect of biostimulant application on production and flavonoid content of marigold (Calendula officinalis L.)

The production of medicinal plants as raw material for industry must associate quality with biomass formation and, with this purpose, the application of plant growth regulators has been studied in these crops. The objective of this study was to evaluate the effect of a biostimulant on growth, inflorescence production and flavonoid content in marigold. The experiment was conducted in a greenhouse and the treatments consisted of increasing doses of the biostimulant (0, 3, 6, 9, 12 and 15 mL L-1) applied by foliar spraying in ten consecutive applications. The experiment was arranged in a completely randomized design, with six treatments and ten repetitions. The number of leaves and flowerheads and dry matter of roots increased linearly with increasing doses of the growth promoter, with 20%, 36.97% and 97.28% increases, respectively, compared with the control. The total dry mass and shoot dry mass showed maximum values at the highest dose tested of 15 mL L-1 (with increases of 40.09% and 46.30%, respectively). Plant height and flavonoid content reached the highest values at a dose of 6 mL L-1. The biostimulant promoted the development of marigold and positively influenced the synthesis of the secondary compound of medicinal interest. Among the tested doses, the application of rates between 6 and 9 mL L-1 of the biostimulant is recommended for more efficient large-scale production of marigold.

Automatic information retrieval through text-mining

The dissertation presented for obtaining the Master’s Degree in Electrical Engineering and Computer Science, at Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Yield of essential oil and safrole content based on fresh and dry biomass of long pepper in the Brazilian Amazon

Long pepper (Piper hispidinervum) is an Amazonian species of commercial interest due to the production of safrole. Drying long pepper biomass to extract safrole is a time consuming and costly process that can also result in the contamination of the material by microorganisms. The objective of this study was to analyze the yield of essential oil and safrole content of fresh and dried biomass of long pepper accessions maintained in the Active Germoplasm Bank of Embrapa Acre, in the state of Acre, Brazil, aiming at selecting genotypes with best performance on fresh biomass to recommend to the breeding program of the species. Yield of essential oil and safrole content were assessed in 15 long pepper accessions. The essential oil extraction was performed by hydrodistillation and analyzed by gas chromatography. A joint analysis of experiments was performed and the means of essential oil yield and safrole content for each biomass were compared by Student's t-test. There was variability in the essential oil yield and safrole content. There was no difference between the types of biomass for oil yield; however to the safrole content there was difference. Populations 9, 10, 12 and 15 had values of oil yield between 4.1 and 5.3%, and safrole content between 87.2 and 94.3%. The drying process does not interfere in oil productivity. These populations have potential for selection to the long pepper breeding program using oil extraction in the fresh biomass

Mining and exploiting domain-specific corpora in the PANACEA platform

The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition,production, updating and maintenance of the large language resources required by, among others, MT systems. The development of a Corpus Acquisition Component (CAC) for extracting monolingual and bilingual data from the web is one of the most innovative building blocks of PANACEA. The CAC, which is the first stage in the PANACEA pipeline for building Language Resources, adopts an efficient and distributed methodology to crawl for web documents with rich textual content in specific languages and predefined domains. The CAC includes modules that can acquire parallel data from sites with in-domain content available in more than one language. In order to extrinsically evaluate the CAC methodology, we have conducted several experiments that used crawled parallel corpora for the identification and extraction of parallel sentences using sentence alignment. The corpora were then successfully used for domain adaptation of Machine Translation Systems.

Physiological responses of two tropical weeds to shade: II. Leaf gas exchange and nitrogen content

Ipomoea asarifolia (Desr.) Roem. & Schultz (Convolvulaceae) and Stachytarpheta cayennensis (Rich) Vahl. (Verbenaceae), two weeds found in pastures and crop areas in the Brazilian Amazonia, Brazil, were grown in controlled environment cabinets under high (800-1000 µmol m-² s-¹) and low (200-350 µmol m-² s-¹) light regimes during a 40-day period. The objective was to determine the effect of shade on photosynthetic features and leaf nitrogen content of I. asarifolia and S. cayennensis. High-irradiance grown I. asarifolia leaves had significantly higher dark respiration and light saturated rates of photosynthesis than low-irradiance leaves. No significant differences for these traits, between treatments, were observed in S. cayennensis. Low-irradiance leaves of both species displayed higher CO2 assimilation rates under low irradiance. High-irradiance grown leaves of both species had less nitrogen per unit of weight. Low-irradiance S. cayennensis had more nitrogen per unit of leaf area than high-irradiance plants; however, I. asarifolia showed no consistent pattern for this variable through time. For S. cayennensis, leaf nitrogen content and CO2 assimilation were inversely correlated to the amount of biomass allocated to developing reproductive structures. These results are discussed in relation to their ecological and weed management implications.

Application of text-mining for updating protein post-translational modification annotation in UniProtKB.

BACKGROUND: The annotation of protein post-translational modifications (PTMs) is an important task of UniProtKB curators and, with continuing improvements in experimental methodology, an ever greater number of articles are being published on this topic. To help curators cope with this growing body of information we have developed a system which extracts information from the scientific literature for the most frequently annotated PTMs in UniProtKB. RESULTS: The procedure uses a pattern-matching and rule-based approach to extract sentences with information on the type and site of modification. A ranked list of protein candidates for the modification is also provided. For PTM extraction, precision varies from 57% to 94%, and recall from 75% to 95%, according to the type of modification. The procedure was used to track new publications on PTMs and to recover potential supporting evidence for phosphorylation sites annotated based on the results of large scale proteomics experiments. CONCLUSIONS: The information retrieval and extraction method we have developed in this study forms the basis of a simple tool for the manual curation of protein post-translational modifications in UniProtKB/Swiss-Prot. Our work demonstrates that even simple text-mining tools can be effectively adapted for database curation tasks, providing that a thorough understanding of the working process and requirements are first obtained. This system can be accessed at http://eagl.unige.ch/PTM/.