Automatic indexing in information retrieval

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Enhancing Information Retrieval by Using Evolution Strategies

Similar to Genetic algorithm, Evolution strategy is a process of continuous reproduction, trial and selection. Each new generation is an improvement on the one that went before. This paper presents two different proposals based on the vector space model (VSM) as a traditional model in information Retrieval (TIR). The first uses evolution strategy (ES). The second uses the document centroid (DC) in query expansion technique. Then the results are compared; it was noticed that ES technique is more efficient than the other methods.

Ontological Approach to Domain Knowledge Representation for Information Retrieval in Multiagent Systems

An ontological representation of buyer interests’ knowledge in process of e-commerce is proposed to use. It makes it more efficient to make a search of the most appropriate sellers via multiagent systems. An algorithm of a comparison of buyer ontology with one of e-shops (the taxonomies) and an e-commerce multiagent system are realised using ontology of information retrieval in distributed environment.

Fast Information Retrieval in the Open Grid Service Architecture

This is an extended version of an article presented at the Second International Conference on Software, Services and Semantic Technologies, Sofia, Bulgaria, 11–12 September 2010.

Using domain-specific knowledge to improve information retrieval performance

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Improving cross language information retrieval using corpus based query suggestion approach

Users seeking information may not find relevant information pertaining to their information need in a specific language. But information may be available in a language different from their own, but users may not know that language. Thus users may experience difficulty in accessing the information present in different languages. Since the retrieval process depends on the translation of the user query, there are many issues in getting the right translation of the user query. For a pair of languages chosen by a user, resources, like incomplete dictionary, inaccurate machine translation system may exist. These resources may be insufficient to map the query terms in one language to its equivalent terms in another language. Also for a given query, there might exist multiple correct translations. The underlying corpus evidence may suggest a clue to select a probable set of translations that could eventually perform a better information retrieval. In this paper, we present a cross language information retrieval approach to effectively retrieve information present in a language other than the language of the user query using the corpus driven query suggestion approach. The idea is to utilize the corpus based evidence of one language to improve the retrieval and re-ranking of news documents in the other language. We use FIRE corpora - Tamil and English news collections in our experiments and illustrate the effectiveness of the proposed cross language information retrieval approach.

Using domain-specific knowledge to improve information retrieval performance

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Vocabulary and language model adaptation using information retrieval

International audience

Semantic Classes in Topic Detection and Tracking

Topic detection and tracking (TDT) is an area of information retrieval research the focus of which revolves around news events. The problems TDT deals with relate to segmenting news text into cohesive stories, detecting something new, previously unreported, tracking the development of a previously reported event, and grouping together news that discuss the same event. The performance of the traditional information retrieval techniques based on full-text similarity has remained inadequate for online production systems. It has been difficult to make the distinction between same and similar events. In this work, we explore ways of representing and comparing news documents in order to detect new events and track their development. First, however, we put forward a conceptual analysis of the notions of topic and event. The purpose is to clarify the terminology and align it with the process of news-making and the tradition of story-telling. Second, we present a framework for document similarity that is based on semantic classes, i.e., groups of words with similar meaning. We adopt people, organizations, and locations as semantic classes in addition to general terms. As each semantic class can be assigned its own similarity measure, document similarity can make use of ontologies, e.g., geographical taxonomies. The documents are compared class-wise, and the outcome is a weighted combination of class-wise similarities. Third, we incorporate temporal information into document similarity. We formalize the natural language temporal expressions occurring in the text, and use them to anchor the rest of the terms onto the time-line. Upon comparing documents for event-based similarity, we look not only at matching terms, but also how near their anchors are on the time-line. Fourth, we experiment with an adaptive variant of the semantic class similarity system. The news reflect changes in the real world, and in order to keep up, the system has to change its behavior based on the contents of the news stream. We put forward two strategies for rebuilding the topic representations and report experiment results. We run experiments with three annotated TDT corpora. The use of semantic classes increased the effectiveness of topic tracking by 10-30\% depending on the experimental setup. The gain in spotting new events remained lower, around 3-4\%. The anchoring the text to a time-line based on the temporal expressions gave a further 10\% increase the effectiveness of topic tracking. The gains in detecting new events, again, remained smaller. The adaptive systems did not improve the tracking results.

Biblioteka Uniwersytecka w Poznaniu w Web 2.0 - rozwój przyjaznej komunikacji cyfrowej i wynikające z niej korzyści

Poster pokazuje metody komunikacji z czytelnikiem stosowane w Bibliotece Uniwersyteckiej w Poznaniu w technologii mediów cyfrowych. Cyfrowe narzędzia komunikacji stały się bardzo pomocne, niemal niezbędne w pozyskiwaniu nowych czytelników, podtrzymywaniu i rozwijaniu współpracy w społeczności w sieci Web.2.0, zarówno tej globalnej, jak i lokalnej akademickiej. Strona WWW jako statyczna komunikacyjnie jest wspierana przez fora dyskusyjne, chaty, wideokonferencje, warsztaty informacyjne, które są prowadzone w czasie rzeczywistym. Twórczą siłę relacji społecznych z biblioteką rozwinęły interaktywne serwisy społecznościowe (Facebook) oraz komunikatory internetowe integrowane na platformie Ask a Librarian. Biblioteka stała się Biblioteką 2.0 ukierunkowaną na komunikację z czytelnikiem. Aktywne uczestnictwo i udział czytelników przy tworzeniu zasobów naukowych wdrożyliśmy w projekcie instytucjonalnego repozytorium - Adam Mickiewicz Repository (AMUR). Biblioteka zmienia się dla czytelników i z czytelnikami. Wykorzystywane platformy i serwisy społecznościowe dostarczają unikatowych danych o nowych potrzebach informacyjnych i oczekiwaniach docelowego Patrona 2.0, co skutkuje doskonaleniu usług istniejących i tworzeniu nowych. Biblioteka monitoruje usługi i potrzeby czytelników przez prowadzone badania społeczne. Technologie cyfrowe stosowane w komunikacji sprawiają, iż biblioteka staje się bliższa, bardziej dostępna, aby stać się w rezultacie partnerem dla stałych i nowych czytelników. Biblioteka Uniwersytecka w Poznaniu bierze udział w programach europejskich w zakresie katalogowania i digitalizacji zasobu biblioteki cyfrowej WBC, w zakresie wdrożenia nowych technologii i rozwiązań podnoszących jakość usług bibliotecznych, działalności kulturotwórczej (Poznańska Dyskusyjna Akademia Kominksu, deBiUty) i edukacji informacyjnej. Biblioteka Uniwersytecka w Poznaniu jest członkiem organizacji międzynarodowych: LIBER (Liga Europejskich Bibliotek Naukowych), IAML (Stowarzyszenie Bibliotek Muzycznych, Archiwów i Ośrodków Dokumentacji), CERL - Europejskie Konsorcjum Bibliotek Naukowych.

Instrumental Fado: a generative interactive system

Fado was listed as UNESCO Intangible Cultural Heritage in 2011. This dissertation describes a theoretical model, as well as an automatic system, able to generate instrumental music based on the musics and vocal sounds typically associated with fado’s practice. A description of the phenomenon of fado, its musics and vocal sounds, based on ethnographic, historical sources and empirical data is presented. The data includes the creation of a digital corpus, of musical transcriptions, identified as fado, and statistical analysis via music information retrieval techniques. The second part consists in the formulation of a theory and the coding of a symbolic model, as a proof of concept, for the automatic generation of instrumental music based on the one in the corpus.

Recuperação de informação de música e dados ID3: possíveis aplicações

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comportamento informacional cotidiano de adolescentes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comportamento informacional cotidiano de adolescentes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)