The increasing flood of documentary information through the Internet and other information sources challenges the developers of information retrieval systems. It is not enough that an IR system is ...able to make a distinction between relevant and non-relevant documents. The reduction of information overload requires that IR systems provide the capability of screening the most valuable documents out of the mass of potentially or marginally relevant documents. This paper introduces a new concept-based method to analyse the text characteristics of documents at varying relevance levels. The results of the document analysis were applied in an experiment on query expansion (QE) in a probabilistic IR system. Statistical differences in textual characteristics of highly relevant and less relevant documents were investigated by applying a facet analysis technique. In highly relevant documents a larger number of aspects of the request were discussed, searchable expressions for the aspects were distributed over a larger set of text paragraphs, and a larger set of unique expressions were used per aspect than in marginally relevant documents. A query expansion experiment verified that the findings of the text analysis can be exploited in formulating more effective queries for best match retrieval in the search for highly relevant documents. The results revealed that expanded queries with concept-based structures performed better than unexpanded queries or Ñnatural languageÒ queries. Further, it was shown that highly relevant documents benefit essentially more from the concept-based QE in ranking than marginally relevant documents.
In order to design information retrieval (IR) learning environments and instruction, it is important to explore learning outcomes of different pedagogical solutions. Learning outcomes have seldom ...been evaluated in IR instruction. The particular focus of this study is the assessment of learning outcomes in an experimental, but naturalistic, learning environment compared to more traditional instruction. The 57 participants of an introductory course on IR were selected for this study, and the analysis illustrates their learning outcomes regarding both conceptual change and development of IR skill. Concept mapping of student essays was used to analyze conceptual change and log-files of search exercises provided data for performance assessment. Students in the experimental learning environment changed their conceptions more regarding linguistic aspects of IR and paid more emphasis on planning and management of search process. Performance assessment indicates that anchored instruction and scaffolding with an instructional tool, the IR Game, with performance feedback enables students to construct queries with fewer semantic knowledge errors also in operational IR systems.
This paper reviews literature on dictionary-based cross-language information retrieval (CLIR) and presents CLIR research done at the University of Tampere (UTA). The main problems associated with ...dictionary-based CLIR, as well as appropriate methods to deal with the problems are discussed. We will present the structured query model by Pirkola and report findings for four different language pairs concerning the effectiveness of query structuring. The architecture of our automatic query translation and construction system is presented. PUBLICATION ABSTRACT
Word form normalization through lemmatization or stemming is a standard procedure in information retrieval because morphological variation needs to be accounted for and several languages are ...morphologically non-trivial. Lemmatization is effective but often requires expensive resources. Stemming is also effective in most contexts, generally almost as good as lemmatization and typically much less expensive; besides it also has a query expansion effect. However, in both approaches the idea is to turn many inflectional word forms to a single lemma or stem both in the database index and in queries. This means extra effort in creating database indexes. This paper takes an opposite approach: it leaves the database index un-normalized and enriches the queries to cover for surface form variation of keywords. The paper shows that the findings are particularly good for short queries that resemble normal searches of web users. This approach is called FCG (for Frequent Case (form) Generation). It can be relatively easily implemented for Latin/Greek/Cyrillic alphabet languages by examining their (typically very skewed) nominal form statistics in a small text sample and by creating surface form generators for the 3-9 most frequent forms. The potential of the FCG approach for several languages of varying morphological complexity is demonstrated.
Introduction. Describes and analyses the information environment of research work in molecular medicine. We presume an interdependence between the information environment, the research process and ...the related work tasks.
Method. This is a qualitative case study using mixed methods. Empirical data were gathered using two surveys and six semi-structured thematic interviews.
Analysis. Analysis was carried out on the merged data of the two surveys. Respondents were divided into groups and information resources were categorized.
Results. The information environment consists of broad categories of data, tools, published material and interpersonal communication. The usage of portals and other integrated resources was substantial. The role of PubMed was central in searching scientific facts. Google was used to locate general Web pages, research groups, methods and tools. Interpersonal communication seemed to be effective in providing information about methods and tools among groups which do laboratory work. The problems reported concerned lack of knowledge about useful resources and how to use them properly, some query formulation problems were also reported, e.g. problems with acronyms, personal names and gene name synonymy.
Conclusions. The information related tasks occupied much of the researchers' time. If information problems were solved, more time to the research would be released. The database and tool interfaces should be easier to use. Introducción. Describe y analiza el entorno de información del trabajo de investigación en medicina molecular. Presumimos una interdependencia entre el entorno de información, el proceso de la investigación y las tareas de trabajo relacionadas.
Método. Éste es un estudio de casos cualitativo que usa métodos mixtos. Se recogieron los datos empíricos usando dos estudios y seis entrevistas temáticas semi-estructuradas.
Análisis. El análisis se realizó sobre los datos fusionados de los dos estudios. Los entrevistados fueron divididos en grupos y se categorizaron los recursos de información.
Resultados. El entorno de información consiste en amplias categorías de datos, herramientas, material publicado y comunicación interpersonal. El uso de portales y otros recursos integrados fue sustancial. El papel de PubMed era central en los hechos de investigación científica. Se usó Google para localizar páginas Web generales, grupos de investigación, métodos y herramientas. La comunicación interpersonal parecía ser efectiva para proporcionar información sobre métodos y herramientas entre grupos que hacen trabajo de laboratorio. Los problemas informados están relacionados con la falta de conocimiento sobre recursos útiles y sobre cómo usarlos apropiadamente, algunos problemas de formulación de consultas también fueron informados, por ejemplo los problemas con siglas, nombres personales y sinonimia de nombres de genes.
Conclusiones. La información relacionada con las tareas, ocuparon mucho tiempo de los investigadores. Si se resolvieran los problemas de información, se liberaría más tiempo para la investigación. La base de datos y las interfaces de las herramientas deben ser más fáciles usar.
We analyze barriers to task‐based information access in molecular medicine, focusing on research tasks, which provide task performance sessions of varying complexity. Molecular medicine is a relevant ...domain because it offers thousands of digital resources as the information environment. Data were collected through shadowing of real work tasks. Thirty work task sessions were analyzed and barriers in these identified. The barriers were classified by their character (conceptual, syntactic, and technological) and by their context of appearance (work task, system integration, or system). Also, work task sessions were grouped into three complexity classes and the frequency of barriers of varying types across task complexity levels were analyzed. Our findings indicate that although most of the barriers are on system level, there is a quantum of barriers in integration and work task contexts. These barriers might be overcome through attention to the integrated use of multiple systems at least for the most frequent uses. This can be done by means of standardization and harmonization of the data and by taking the requirements of the work tasks into account in system design and development, because information access is seldom an end itself, but rather serves to reach the goals of work tasks.
Semantic associations are direct or indirect linkages between two entities that are construed from existing associations among entities. In this paper we extend our previous query language approach ...for discovering semantic associations with an ability to retrieve semantic associations that, besides explicitly stated (base) associations, may contain associations derived using logic-based derivation rules. As will be shown, this makes it possible to find semantic associations that are both compact and intuitive. To implement this new feature, we introduce a rewriting principle that utilizes derived associations to reduce resulting semantic associations if possible. Other proposed means to assist the interpretation of query results include answer expansion and the ordering of answers. The incorporated answer expansion feature lets the user investigate rewritten semantic associations in a query result at the desired level of detail. The ordering of answers is based on the lengths of the resulting semantic associations, whereby priority is given to shorter semantic associations which often express close and relevant relationships.
Purpose - The aim of this paper is to explore the possibility of retrieving information with Kohonen self-organising maps, which are known to be effective to group objects according to their ...similarity or dissimilarity.Design methodology approach - After conventional preprocessing, such as transforming into vector space, documents from a German document collection were trained for a neural network of Kohonen self-organising map type. Such an unsupervised network forms a document map from which relevant objects can be found according to queries.Findings - Self-organising maps ordered documents to groups from which it was possible to find relevant targets.Research limitations implications - The number of documents used was moderate due to the limited number of documents associated to test topics. The training of self-organising maps entails rather long running times, which is their practical limitation. In future, the aim will be to build larger networks by compressing document matrices, and to develop document searching in them.Practical implications - With self-organising maps the distribution of documents can be visualised and relevant documents found in document collections of limited size.Originality value - The paper reports on an approach that can be especially used to group documents and also for information search. So far self-organising maps have rarely been studied for information retrieval. Instead, they have been applied to document grouping tasks.
There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an ...integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.
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