Literatur zur Informationserschließung

Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.

© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 13. Juni 2017)

Suchergebnisse

• 1
  Li, N. ; Sun, J.: Improving Chinese term association from the linguistic perspective.
  In: Knowledge organization. 44(2017) no.1, S.13-23.
  
  Abstract: The study aims to solve how to construct the semantic relations of specific domain terms by applying linguistic rules. The semantic structure analysis at the morpheme level was used for semantic measure, and a morpheme-based term association model was proposed by improving and combining the literal-based similarity algorithm and co-occurrence relatedness methods. This study provides a novel insight into the method of semantic analysis and calculation by morpheme parsing, and the proposed solution is feasible for the automatic association of compound terms. The results show that this approach could be used to construct appropriate term association and form a reasonable structural knowledge graph. However, due to linguistic differences, the viability and effectiveness of the use of our method in non-Chinese linguistic environments should be verified.
  
  Themenfeld: Semantisches Umfeld in Indexierung u. Retrieval ; Computerlinguistik
  
  
• 2
  AL-Smadi, M. ; Jaradat, Z. ; AL-Ayyoub, M. ; Jararweh, Y.: Paraphrase identification and semantic text similarity analysis in Arabic news tweets using lexical, syntactic, and semantic features.
  In: Information processing and management. 53(2017) no.3, S.640-652.
  
  Abstract: The rapid growth in digital information has raised considerable challenges in particular when it comes to automated content analysis. Social media such as twitter share a lot of its users' information about their events, opinions, personalities, etc. Paraphrase Identification (PI) is concerned with recognizing whether two texts have the same/similar meaning, whereas the Semantic Text Similarity (STS) is concerned with the degree of that similarity. This research proposes a state-of-the-art approach for paraphrase identification and semantic text similarity analysis in Arabic news tweets. The approach adopts several phases of text processing, features extraction and text classification. Lexical, syntactic, and semantic features are extracted to overcome the weakness and limitations of the current technologies in solving these tasks for the Arabic language. Maximum Entropy (MaxEnt) and Support Vector Regression (SVR) classifiers are trained using these features and are evaluated using a dataset prepared for this research. The experimentation results show that the approach achieves good results in comparison to the baseline results.
  
  Inhalt: Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457316302382.
  
  Themenfeld: Computerlinguistik
  
  
• 3
  Lu, K. ; Cai, X. ; Ajiferuke, I. ; Wolfram, D.: Vocabulary size and its effect on topic representation.
  In: Information processing and management. 53(2017) no.3, S.653-665.
  
  Abstract: This study investigates how computational overhead for topic model training may be reduced by selectively removing terms from the vocabulary of text corpora being modeled. We compare the impact of removing singly occurring terms, the top 0.5%, 1% and 5% most frequently occurring terms and both top 0.5% most frequent and singly occurring terms, along with changes in the number of topics modeled (10, 20, 30, 40, 50, 100) using three datasets. Four outcome measures are compared. The removal of singly occurring terms has little impact on outcomes for all of the measures tested. Document discriminative capacity, as measured by the document space density, is reduced by the removal of frequently occurring terms, but increases with higher numbers of topics. Vocabulary size does not greatly influence entropy, but entropy is affected by the number of topics. Finally, topic similarity, as measured by pairwise topic similarity and Jensen-Shannon divergence, decreases with the removal of frequent terms. The findings have implications for information science research in information retrieval and informetrics that makes use of topic modeling.
  
  Inhalt: Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457317300298.
  
  Themenfeld: Computerlinguistik
  
  
• 4
  Engerer, V.: Exploring interdisciplinary relationships between linguistics and information retrieval from the 1960s to today.
  In: Journal of the Association for Information Science and Technology. 67(2017) no.3, S.660-680.
  
  Abstract: This article explores how linguistics has influenced information retrieval (IR) and attempts to explain the impact of linguistics through an analysis of internal developments in information science generally, and IR in particular. It notes that information science/IR has been evolving from a case science into a fully fledged, "disciplined"/disciplinary science. The article establishes correspondences between linguistics and information science/IR using the three established IR paradigms-physical, cognitive, and computational-as a frame of reference. The current relationship between information science/IR and linguistics is elucidated through discussion of some recent information science publications dealing with linguistic topics and a novel technique, "keyword collocation analysis," is introduced. Insights from interdisciplinarity research and case theory are also discussed. It is demonstrated that the three stages of interdisciplinarity, namely multidisciplinarity, interdisciplinarity (in the narrow sense), and transdisciplinarity, can be linked to different phases of the information science/IR-linguistics relationship and connected to different ways of using linguistic theory in information science and IR.
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23684/full [DOI: 10.1002/asi.23684].
  
  Themenfeld: Computerlinguistik ; Geschichte der Sacherschließung
  
  
• 5
  Rozinajová, V. ; Macko, P.: Using natural language to search linked data.
  In: Semantic keyword-based search on structured data sources: COST Action IC1302. Second International KEYSTONE Conference, IKC 2016, Cluj-Napoca, Romania, September 8-9, 2016, Revised Selected Papers. Eds.: A. Calì, A. et al. Springer International Publishing, 2017. S.179-189.
  (Information Systems and Applications, incl. Internet/Web, and HCI; 10151)
  
  Abstract: There are many endeavors aiming to offer users more effective ways of getting relevant information from web. One of them is represented by a concept of Linked Data, which provides interconnected data sources. But querying these types of data is difficult not only for the conventional web users but also for ex-perts in this field. Therefore, a more comfortable way of user query would be of great value. One direction could be to allow the user to use a natural language. To make this task easier we have proposed a method for translating natural language query to SPARQL query. It is based on a sentence structure - utilizing dependen-cies between the words in user queries. Dependencies are used to map the query to the semantic web structure, which is in the next step translated to SPARQL query. According to our first experiments we are able to answer a significant group of user queries.
  
  Inhalt: Vgl. auch: http://www.keystone-cost.eu/ikc2016/program.php.
  
  Themenfeld: Computerlinguistik
  
  
• 6
  Babik, W.: Keywords as linguistic tools in information and knowledge organization.
  In: Theorie, Semantik und Organisation von Wissen: Proceedings der 13. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und dem 13. Internationalen Symposium der Informationswissenschaft der Higher Education Association for Information Science (HI) Potsdam (19.-20.03.2013): 'Theory, Information and Organization of Knowledge' / Proceedings der 14. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und Natural Language & Information Systems (NLDB) Passau (16.06.2015): 'Lexical Resources for Knowledge Organization' / Proceedings des Workshops der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) auf der SEMANTICS Leipzig (1.09.2014): 'Knowledge Organization and Semantic Web' / Proceedings des Workshops der Polnischen und Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) Cottbus (29.-30.09.2011): 'Economics of Knowledge Production and Organization'. Hrsg. von W. Babik, H.P. Ohly u. K. Weber. Würzburg : Ergon Verlag, 2017. S.306-313.
  (Fortschritte in der Wissensorganisation; Bd.13)
  
  Themenfeld: Computerlinguistik
  
  
• 7
  Collovini de Abreu, S. ; Vieira, R.: RelP: Portuguese open relation extraction.
  In: Knowledge organization. 44(2017) no.3, S.163-177.
  
  Abstract: Natural language texts are valuable data sources in many human activities. NLP techniques are being widely used in order to help find the right information to specific needs. In this paper, we present one such technique: relation extraction from texts. This task aims at identifying and classifying semantic relations that occur between entities in a text. For example, the sentence "Roberto Marinho is the founder of Rede Globo" expresses a relation occurring between "Roberto Marinho" and "Rede Globo." This work presents a system for Portuguese Open Relation Extraction, named RelP, which extracts any relation descriptor that describes an explicit relation between named entities in the organisation domain by applying the Conditional Random Fields. For implementing RelP, we define the representation scheme, features based on previous work, and a reference corpus. RelP achieved state of the art results for open relation extraction; the F-measure rate was around 60% between the named entities person, organisation and place. For better understanding of the output, we present a way for organizing the output from the mining of the extracted relation descriptors. This organization can be useful to classify relation types, to cluster the entities involved in a common relation and to populate datasets.
  
  Inhalt: Beitrag in einem Special Issue "New Trends for Knowledge Organization, Guest Editor: Renato Rocha Souza".
  
  Themenfeld: Computerlinguistik
  
  
• 8
  Perovsek, M. ; Kranjca, J. ; Erjaveca, T. ; Cestnika, B. ; Lavraca, N.: TextFlows : a visual programming platform for text mining and natural language processing.
  In: Science of computer programming. In Press, 2016.
  
  Abstract: Text mining and natural language processing are fast growing areas of research, with numerous applications in business, science and creative industries. This paper presents TextFlows, a web-based text mining and natural language processing platform supporting workflow construction, sharing and execution. The platform enables visual construction of text mining workflows through a web browser, and the execution of the constructed workflows on a processing cloud. This makes TextFlows an adaptable infrastructure for the construction and sharing of text processing workflows, which can be reused in various applications. The paper presents the implemented text mining and language processing modules, and describes some precomposed workflows. Their features are demonstrated on three use cases: comparison of document classifiers and of different part-of-speech taggers on a text categorization problem, and outlier detection in document corpora.
  
  Inhalt: Vgl.: http://www.sciencedirect.com/science/article/pii/S0167642316000113. Vgl. auch: http://textflows.org.
  
  Themenfeld: Computerlinguistik
  Objekt: TextFlows
  
  
• 9
  Radev, D.R. ; Joseph, M.T. ; Gibson, B. ; Muthukrishnan, P.: ¬A bibliometric and network analysis of the field of computational linguistics.
  In: Journal of the Association for Information Science and Technology. 67(2016) no.3, S.683-706.
  
  Abstract: The ACL Anthology is a large collection of research papers in computational linguistics. Citation data were obtained using text extraction from a collection of PDF files with significant manual postprocessing performed to clean up the results. Manual annotation of the references was then performed to complete the citation network. We analyzed the networks of paper citations, author citations, and author collaborations in an attempt to identify the most central papers and authors. The analysis includes general network statistics, PageRank, metrics across publication years and venues, the impact factor and h-index, as well as other measures.
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23394/abstract.
  
  Themenfeld: Informetrie ; Computerlinguistik
  
  
• 10
  Baierer, K. ; Zumstein, P.: Verbesserung der OCR in digitalen Sammlungen von Bibliotheken.
  In: 027.7 Zeitschrift für Bibliothekskultur. 4(2016), H.2.
  
  Abstract: Möglichkeiten zur Verbesserung der automatischen Texterkennung (OCR) in digitalen Sammlungen insbesondere durch computerlinguistische Methoden werden beschrieben und bisherige PostOCR-Verfahren analysiert. Im Gegensatz zu diesen Möglichkeiten aus der Forschung oder aus einzelnen Projekten unterscheidet sich die momentane Anwendung von OCR in der Bibliothekspraxis wesentlich und nutzt das Potential nur teilweise aus.
  
  Inhalt: Beitrag in einem Themenschwerpunkt 'Computerlinguistik und Bibliotheken'. Vgl.: http://0277.ch/ojs/index.php/cdrs_0277/article/view/155/353.
  
  Themenfeld: Computerlinguistik
  Hilfsmittel: OCR
  
  
• 11
  Menge-Sonnentag, R.: Google veröffentlicht einen Parser für natürliche Sprache.
  In: heise Developer (13.05.2016), [http://www.heise.de/developer/meldung/Google-veroeffentlicht-einen-Parser-fuer-natuerliche-Sprache-3207846.html].
  
  Abstract: SyntaxNet zerlegt Sätze in ihre grammatikalischen Bestandteile und bestimmt die syntaktischen Beziehungen der Wörter untereinander. Das Framework ist Open Source und als TensorFlow Model implementiert. Ein Parser für natürliche Sprache ist eine Software, die Sätze in ihre grammatikalischen Bestandteile zerlegt. Diese Zerlegung ist notwendig, damit Computer Befehle verstehen oder Texte übersetzen können. Die digitalen Helfer wie Microsofts Cortana, Apples Siri und Google Now verwenden Parser, um Sätze wie "Stell den Wecker auf 5 Uhr!" richtig umzusetzen. SyntaxNet ist ein solcher Parser, den Google als TensorFlow Model veröffentlicht hat. Entwickler können eigene Modelle erstellen, und SnytaxNet bringt einen vortrainierten Parser für die englische Sprache mit, den seine Macher Parsey McParseface genannt haben.
  
  Inhalt: "Syntaktische Beziehungen Der Parser teilt den Wörtern eine syntaktische Funktion zu und untersucht die syntaktischen Beziehungen zwischen den Einzelteilen. Den englischen Beispielsatz aus dem Blog-Beitrag "Alice saw Bob" analysiert er folgendermaßen: "Alice" und "Bob" sind Substantive, und "saw" ist ein Verb. Letzteres ist gleichzeitig die Wurzel (ROOT), von der die restlichen Beziehungen ausgehen. Alice ist das zugehörige Subjekt (nsubj) und Bob das Objekt (dobj). Längere Sätze werden leicht mehrdeutig. Beispielsweise ist im Satz "Alice sah Bob mit dem Fernglas" nicht erkennbar, wer von den beiden das Fernglas in der Hand hält. Rein syntaktisch ist auch der Satz "Peter schneidet das Brot mit Sonnenblumenkernen" mehrdeutig. Das menschliche Gehirn erkennt die richtige Bedeutung recht zuverlässig, aber für maschinelle Parser stellen sie eine Herausforderung dar. ; SyntaxNet nutzt zur Entscheidung neuronale Netze und versucht die Abhängigkeiten richtig zuzuordnen. Damit "lernt" der Parser, dass es schwierig ist, Sonnenblumenkerne zum Schneiden einzusetzen, und sie somit wohl eher Bestandteil des Brots als ein Werkzeug sind. Die Analyse beschränkt sich jedoch auf den Satz selbst. Semantische Zusammenhänge berücksichtigt das Modell nicht. So lösen sich manche Mehrdeutigkeiten durch den Kontext auf: Wenn Alice im obigen Beispiel das Fernglas beim Verlassen des Hauses eingepackt hat, wird sie es vermutlich benutzen. Trefferquote Mensch vs. Maschine Laut dem Blog-Beitrag kommt Parsey McParseface auf eine Genauigkeit von gut 94 Prozent für Sätze aus dem Penn Treebank Project. Die menschliche Quote soll laut Linguisten bei 96 bis 97 Prozent liegen. Allerdings weist der Beitrag auch darauf hin, dass es sich bei den Testsätzen um wohlgeformte Texte handelt. Im Test mit Googles WebTreebank erreicht der Parser eine Genauigkeit von knapp 90 Prozent."
  
  Anmerkung: Download unter: https://github.com/tensorflow/models/tree/master/syntaxnet. Dort befinden sich auch weitere Information zu dem Modell sowie Vergleichszahlen zur Erkennungsrate.
  
  Themenfeld: Computerlinguistik
  Objekt: SyntaxNet
  
  
• 12
  Savoy, J.: Text representation strategies : an example with the State of the union addresses.
  In: Journal of the Association for Information Science and Technology. 67(2016) no.8, S.1858-1870.
  
  Abstract: Based on State of the Union addresses from 1790 to 2014 (225 speeches delivered by 42 presidents), this paper describes and evaluates different text representation strategies. To determine the most important words of a given text, the term frequencies (tf) or the tf?idf weighting scheme can be applied. Recently, latent Dirichlet allocation (LDA) has been proposed to define the topics included in a corpus. As another strategy, this study proposes to apply a vocabulary specificity measure (Z?score) to determine the most significantly overused word-types or short sequences of them. Our experiments show that the simple term frequency measure is not able to discriminate between specific terms associated with a document or a set of texts. Using the tf idf or LDA approach, the selection requires some arbitrary decisions. Based on the term-specific measure (Z?score), the term selection has a clear theoretical basis. Moreover, the most significant sentences for each presidency can be determined. As another facet, we can visualize the dynamic evolution of usage of some terms associated with their specificity measures. Finally, this technique can be employed to define the most important lexical leaders introducing terms overused by the k following presidencies.
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23510/abstract.
  
  Themenfeld: Computerlinguistik
  
  
• 13
  Lian, T. ; Yu, C. ; Wang, W. ; Yuan, Q. ; Hou, Z.: Doctoral dissertations on tourism in China : a co-word analysis.
  In: Knowledge organization. 43(2016) no.6, S.440-461.
  
  Abstract: The aim of this paper is to map the foci of research in doctoral dissertations on tourism in China. In the paper, coword analysis is applied, with keywords coming from six public dissertation databases, i.e. CDFD, Wanfang Data, NLC, CALIS, ISTIC, and NSTL, as well as some university libraries providing doctoral dissertations on tourism. Altogether we have examined 928 doctoral dissertations on tourism written between 1989 and 2013. Doctoral dissertations on tourism in China involve 36 first level disciplines and 102 secondary level disciplines. We collect the top 68 keywords of practical significance in tourism which are mentioned at least four times or more. These keywords are classified into 12 categories based on co-word analysis, including cluster analysis, strategic diagrams analysis, and social network analysis. According to the strategic diagram of the 12 categories, we find the mature and immature areas in tourism study. From social networks, we can see the social network maps of original co-occurrence matrix and k-cores analysis of binary matrix. The paper provides valuable insight into the study of tourism by analyzing doctoral dissertations on tourism in China.
  
  Themenfeld: Computerlinguistik
  Behandelte Form: Dissertationen
  Land/Ort: China
  
  
• 14
  Bredack, J.: Automatische Extraktion fachterminologischer Mehrwortbegriffe : ein Verfahrensvergleich.
  Trier : Universität / Fachbereich II, 2016. V, 98 S.
  
  Abstract: In dieser Untersuchung wurden zwei Systeme eingesetzt, um MWT aus einer Dokumentkollektion mit fachsprachlichem Bezug (Volltexte des ACL Anthology Reference Corpus) automatisch zu extrahieren. Das thematische Spektrum umfasste alle Bereiche der natürlichen Sprachverarbeitung, im Speziellen die CL als interdisziplinäre Wissenschaft. Ziel war es MWT zu extrahieren, die als potentielle Indexterme im IR Verwendung finden können. Diese sollten auf Konzepte, Methoden, Verfahren und Algorithmen in der CL und angrenzenden Teilgebieten, wie Linguistik und Informatik hinweisen bzw. benennen. ; Als Extraktionssysteme wurden der TreeTagger und die Indexierungssoftware Lingo verwendet. Der TreeTagger basiert auf einem statistischen Tagging- und Chunking- Algorithmus, mit dessen Hilfe NPs automatisch identifiziert und extrahiert werden. Er kann für verschiedene Anwendungsszenarien der natürlichen Sprachverarbeitung eingesetzt werden, in erster Linie als POS-Tagger für unterschiedliche Sprachen. Das Indexierungssystem Lingo arbeitet im Gegensatz zum TreeTagger mit elektronischen Wörterbüchern und einem musterbasierten Abgleich. Lingo ist ein auf automatische Indexierung ausgerichtetes System, was eine Vielzahl von Modulen mitliefert, die individuell auf eine bestimmte Aufgabenstellung angepasst und aufeinander abgestimmt werden können. Die unterschiedlichen Verarbeitungsweisen haben sich in den Ergebnismengen beider Systeme deutlich gezeigt. Die gering ausfallenden Übereinstimmungen der Ergebnismengen verdeutlichen die abweichende Funktionsweise und konnte mit einer qualitativen Analyse beispielhaft beschrieben werden. In der vorliegenden Arbeit kann abschließend nicht geklärt werden, welches der beiden Systeme bevorzugt für die Generierung von Indextermen eingesetzt werden sollte.
  
  Inhalt: Schriftliche Hausarbeit (Masterarbeit) zur Erlangung des Grades eines Master of Arts An der Universität Trier Fachbereich II Studiengang Computerlinguistik.
  
  Themenfeld: Automatisches Indexieren ; Computerlinguistik
  Objekt: Lingo ; TreeTagger
  
  
• 15
  Ledl, A. (Hrsg.): Franke-Maier, M.: Computerlinguistik und Bibliotheken : Editorial.
  In: 027.7 Zeitschrift für Bibliothekskultur. 4(2016), H.2.
  
  Abstract: Vor 50 Jahren, im Februar 1966, wies Floyd M. Cammack auf den Zusammenhang von "Linguistics and Libraries" hin. Er ging dabei von dem Eintrag für "Linguistics" in den Library of Congress Subject Headings (LCSH) von 1957 aus, der als Verweis "See Language and Languages; Philology; Philology, Comparative" enthielt. Acht Jahre später kamen unter dem Schlagwort "Language and Languages" Ergänzungen wie "language data processing", "automatic indexing", "machine translation" und "psycholinguistics" hinzu. Für Cammack zeigt sich hier ein Netz komplexer Wechselbeziehungen, die unter dem Begriff "Linguistics" zusammengefasst werden sollten. Dieses System habe wichtigen Einfluss auf alle, die mit dem Sammeln, Organisieren, Speichern und Wiederauffinden von Informationen befasst seien. (Cammack 1966:73). Hier liegt - im übertragenen Sinne - ein Heft vor Ihnen, in dem es um computerlinguistische Verfahren in Bibliotheken geht. Letztlich geht es um eine Versachlichung der Diskussion, um den Stellenwert der Inhaltserschliessung und die Rekalibrierung ihrer Wertschätzung in Zeiten von Mega-Indizes und Big Data. Der derzeitige Widerspruch zwischen dem Wunsch nach relevanter Treffermenge in Rechercheoberflächen vs. der Erfahrung des Relevanz-Rankings ist zu lösen. Explizit auch die Frage, wie oft wir von letzterem enttäuscht wurden und was zu tun ist, um das Verhältnis von recall und precision wieder in ein angebrachtes Gleichgewicht zu bringen. Unsere Nutzerinnen und Nutzer werden es uns danken.
  
  Inhalt: Editorial zu einem Themenschwerpunkt 'Computerlinguistik und Bibliotheken'. Vgl-: http://0277.ch/ojs/index.php/cdrs_0277/article/view/159/349.
  
  Themenfeld: Computerlinguistik
  
  
• 16
  Lhadj, L.S. ; Boughanem, M. ; Amrouche, K.: Enhancing information retrieval through concept-based language modeling and semantic smoothing.
  In: Journal of the Association for Information Science and Technology. 67(2016) no.12, S.2909-2927.
  
  Abstract: Traditionally, many information retrieval models assume that terms occur in documents independently. Although these models have already shown good performance, the word independency assumption seems to be unrealistic from a natural language point of view, which considers that terms are related to each other. Therefore, such an assumption leads to two well-known problems in information retrieval (IR), namely, polysemy, or term mismatch, and synonymy. In language models, these issues have been addressed by considering dependencies such as bigrams, phrasal-concepts, or word relationships, but such models are estimated using simple n-grams or concept counting. In this paper, we address polysemy and synonymy mismatch with a concept-based language modeling approach that combines ontological concepts from external resources with frequently found collocations from the document collection. In addition, the concept-based model is enriched with subconcepts and semantic relationships through a semantic smoothing technique so as to perform semantic matching. Experiments carried out on TREC collections show that our model achieves significant improvements over a single word-based model and the Markov Random Field model (using a Markov classifier).
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23553/full.
  
  Themenfeld: Computerlinguistik
  
  
• 17
  Järvelin, A. ; Keskustalo, H. ; Sormunen, E. ; Saastamoinen, M. ; Kettunen, K.: Information retrieval from historical newspaper collections in highly inflectional languages : a query expansion approach.
  In: Journal of the Association for Information Science and Technology. 67(2016) no.12, S.2928-2946.
  
  Abstract: The aim of the study was to test whether query expansion by approximate string matching methods is beneficial in retrieval from historical newspaper collections in a language rich with compounds and inflectional forms (Finnish). First, approximate string matching methods were used to generate lists of index words most similar to contemporary query terms in a digitized newspaper collection from the 1800s. Top index word variants were categorized to estimate the appropriate query expansion ranges in the retrieval test. Second, the effectiveness of approximate string matching methods, automatically generated inflectional forms, and their combinations were measured in a Cranfield-style test. Finally, a detailed topic-level analysis of test results was conducted. In the index of historical newspaper collection the occurrences of a word typically spread to many linguistic and historical variants along with optical character recognition (OCR) errors. All query expansion methods improved the baseline results. Extensive expansion of around 30 variants for each query word was required to achieve the highest performance improvement. Query expansion based on approximate string matching was superior to using the inflectional forms of the query words, showing that coverage of the different types of variation is more important than precision in handling one type of variation.
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23379/full.
  
  Themenfeld: Computerlinguistik ; Semantisches Umfeld in Indexierung u. Retrieval
  Behandelte Form: Zeitungen
  
  
• 18
  Schmolz, H.: Anaphora resolution and text retrieval : a lnguistic analysis of hypertexts.
  Berlin : De Gruyter Mouton, 2015. VIII, 280 S.
  ISBN 978-3-11-041674-9
  (Empirische Linguistik / Empirical Linguistics ; 3)
  
  Anmerkung: Überarbeitete Version der Doktorarbeit, Universität Passau, 2013.
  
  Themenfeld: Computerlinguistik ; Hypertext
  
  RSWK: Englisch / Anapher / Hypertext / Information Retrieval / Korpus
  DDC: 400
  RVK: HF 450 ; HF 342
  
• 19
  Kim, S. ; Ko, Y. ; Oard, D.W.: Combining lexical and statistical translation evidence for cross-language information retrieval.
  In: Journal of the Association for Information Science and Technology. 66(2015) no.1, S.23-39.
  
  Abstract: This article explores how best to use lexical and statistical translation evidence together for cross-language information retrieval (CLIR). Lexical translation evidence is assembled from Wikipedia and from a large machine-readable dictionary, statistical translation evidence is drawn from parallel corpora, and evidence from co-occurrence in the document language provides a basis for limiting the adverse effect of translation ambiguity. Coverage statistics for NII Testbeds and Community for Information Access Research (NTCIR) queries confirm that these resources have complementary strengths. Experiments with translation evidence from a small parallel corpus indicate that even rather rough estimates of translation probabilities can yield further improvements over a strong technique for translation weighting based on using Jensen-Shannon divergence as a term-association measure. Finally, a novel approach to posttranslation query expansion using a random walk over the Wikipedia concept link graph is shown to yield further improvements over alternative techniques for posttranslation query expansion. Evaluation results on the NTCIR-5 English-Korean test collection show statistically significant improvements over strong baselines.
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23153/abstract.
  
  Themenfeld: Computerlinguistik ; Multilinguale Probleme
  
  
• 20
  Ramisch, C.: Multiword expressions acquisition : a generic and open framework.
  Cham : Springer International Publishing, 2015. XIV, 230 S.
  ISBN 978-3-319-09206-5
  (Theory and applications of natural language processing)
  
  Abstract: This book is an excellent introduction to multiword expressions. It provides a unique, comprehensive and up-to-date overview of this exciting topic in computational linguistics. The first part describes the diversity and richness of multiword expressions, including many examples in several languages. These constructions are not only complex and arbitrary, but also much more frequent than one would guess, making them a real nightmare for natural language processing applications. The second part introduces a new generic framework for automatic acquisition of multiword expressions from texts. Furthermore, it describes the accompanying free software tool, the mwetoolkit, which comes in handy when looking for expressions in texts (regardless of the language). Evaluation is greatly emphasized, underlining the fact that results depend on parameters like corpus size, language, MWE type, etc. The last part contains solid experimental results and evaluates the mwetoolkit, demonstrating its usefulness for computer-assisted lexicography and machine translation. This is the first book to cover the whole pipeline of multiword expression acquisition in a single volume. It is addresses the needs of students and researchers in computational and theoretical linguistics, cognitive sciences, artificial intelligence and computer science. Its good balance between computational and linguistic views make it the perfect starting point for anyone interested in multiword expressions, language and text processing in general.
  
  Inhalt: 1.Introduction.- Part I.Multiword Expressions: a Tough Nut to Crack.- 2.Definitions and Characteristics.- 3 State of the Art in MWE Processing.- Part II.MWE Acquisition.- 4.Evaluation of MWE Acquisition.- 5.A New Framework for MWE Acquisition.- Part III Applications.- 6.Application 1: Lexicography.- 7.Application 2: Machine Translation.- 8.Conclusions.- Appendixes.- A.Extended List of Translation Examples.- B.Resources Used in the Experiments.- C.The mwetoolkit: Documentation.- D.Tagsets for POS and syntax.- E.Detailed Lexicon Descriptions.
  
  Anmerkung: Bemerkung im Katalog der DNB: "Gehoert eindeutig nicht zum Sammelgebiet der Deutschen Nationalbibliothek"
  
  Themenfeld: Computerlinguistik
  
  GHBS: BFP (FH K)