A Plugin Architecture Enabling Federated Search for Digital Libraries

Chernov, Sergey; Kohlschütter, Christian; Nejdl, Wolfgang

doi:10.1007/11931584_23

Cited by 3 publications

(3 citation statements)

References 12 publications

(11 reference statements)

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“…Considering post-retrieval approaches, a simple method is to organise the results randomly, as in (Chernov et al, 2006). Another common approach is the reordering of results based on their scores, but this implies that scoring criteria must be unified, in order to be homogeneous among different REs.…”

Section: How Results Are Mergedmentioning

confidence: 99%

“…It transcribes the query, and matches it against the information extracted from videos. Some more complex techniques can be found in (Chernov et al, 2006), which implements a broker (handler) to select the systems to be activated, depending on the terms present in the query. A probabilistic approach to selecting REs, depending on the relevant entities that each engine would return, is presented in (Balog et al, 2012).…”

Section: Selecting Different Retrieval Enginesmentioning

confidence: 99%

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Combining heterogeneous sources in an interactive multimedia content retrieval model

Schneider¹,

Martı́nez

Martínez-Fernández³

2017

Expert Systems with Applications

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Interactive multimodal information retrieval systems (IMIR) increase the capabilities of traditional search systems, by adding the ability to retrieve information of different types (modes) and from different sources. This article describes a formal model for interactive multimodal information retrieval. This model includes formal and widespread definitions of each component of an IMIR system. A use case that focuses on information retrieval regarding sports validates the model, by developing a prototype that implements a subset of the features of the model. Adaptive techniques applied to the retrieval functionality of IMIR systems have been defined by analysing past interactions using decision trees, neural networks, and clustering techniques. This model includes a strategy for selecting sources and combining the results obtained from every source. After modifying the strategy of the prototype for selecting sources, the system is re-evaluated using classification techniques. This evaluation compares the normalised discounted cumulative gain (NDCG) measure obtained using two different approaches: the multimodal system using a baseline strategy based on predefined rules as a source selection strategy, and the same multimodal system with the functionality adapted by past user interactions. In the adapted system, a final value of 81,54% was obtained for the NDCG.

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Section: How Results Are Mergedmentioning

confidence: 99%

Section: Selecting Different Retrieval Enginesmentioning

confidence: 99%

Combining heterogeneous sources in an interactive multimedia content retrieval model

Schneider¹,

Martı́nez

Martínez-Fernández³

2017

Expert Systems with Applications

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“…The stick-like connection between two proteins indicates their interaction relationship. Based on the inter-library web service search framework [ 22 ], PPLook provides a heterogeneous search engines [ 23 ] that can link to the PDB search engine and Google search engine, thus letting users directly proceed to online search to gather related information about their proteins of interest.…”

Section: Methodsmentioning

confidence: 99%

PPLook: an automated data mining tool for protein-protein interaction

Zhang

Xia

et al. 2010

BMC Bioinformatics

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BackgroundExtracting and visualizing of protein-protein interaction (PPI) from text literatures are a meaningful topic in protein science. It assists the identification of interactions among proteins. There is a lack of tools to extract PPI, visualize and classify the results.ResultsWe developed a PPI search system, termed PPLook, which automatically extracts and visualizes protein-protein interaction (PPI) from text. Given a query protein name, PPLook can search a dataset for other proteins interacting with it by using a keywords dictionary pattern-matching algorithm, and display the topological parameters, such as the number of nodes, edges, and connected components. The visualization component of PPLook enables us to view the interaction relationship among the proteins in a three-dimensional space based on the OpenGL graphics interface technology. PPLook can also provide the functions of selecting protein semantic class, counting the number of semantic class proteins which interact with query protein, counting the literature number of articles appearing the interaction relationship about the query protein. Moreover, PPLook provides heterogeneous search and a user-friendly graphical interface.ConclusionsPPLook is an effective tool for biologists and biosystem developers who need to access PPI information from the literature. PPLook is freely available for non-commercial users at http://meta.usc.edu/softs/PPLook.

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