Search (2 results, page 1 of 1)

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Abstract

This article describes two approaches for searching heterogeneous resources, which are explained as they are used in two corresponding existing systems-RIRS (Resource Integration Retrieval System) and HRUSP (Heterogeneous Resource Union Search Platform). On analyzing the existing systems, a possible framework-the MUSP (Multimetadata-Based Union Search Platform) is presented. Libraries now face a dilemma. On one hand, libraries subscribe to many types of database retrieval systems that are produced by various providers. The libraries build their data and information systems independently. This results in highly heterogeneous and distributed systems at the technical level (e.g., different operating systems and user interfaces) and at the conceptual level (e.g., the same objects are named using different terms). On the other hand, end users want to access all these heterogeneous data via a union interface, without having to know the structure of each information system or the different retrieval methods used by the systems. Libraries must achieve a harmony between information providers and users. In order to bridge the gap between the service providers and the users, it would seem that all source databases would need to be rebuilt according to a uniform data structure and query language, but this seems impossible. Fortunately, however, libraries and information and technology providers are now making an effort to find a middle course that meets the requirements of both data providers and users. They are doing this through resource integration.

Type

a

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Abstract

With the popularity of online educational platforms, English learners can learn and practice no matter where they are and what they do. English grammar is one of the important components in learning English. To learn English grammar effectively, it requires students to practice questions containing focused grammar knowledge. In this paper, we study a novel problem of retrieving English grammar questions with similar grammatical focus. Since the grammatical focus similarity is different from textual similarity or sentence syntactic similarity, existing approaches cannot be applied directly to our problem. To address this problem, we propose a syntactic based approach for English grammar question retrieval which can retrieve related grammar questions with similar grammatical focus effectively. In the proposed syntactic based approach, we first propose a new syntactic tree, namely parse-key tree, to capture English grammar questions' grammatical focus. Next, we propose two kernel functions, namely relaxed tree kernel and part-of-speech order kernel, to compute the similarity between two parse-key trees of the query and grammar questions in the collection. Then, the retrieved grammar questions are ranked according to the similarity between the parse-key trees. In addition, if a query is submitted together with answer choices, conceptual similarity and textual similarity are also incorporated to further improve the retrieval accuracy. The performance results have shown that our proposed approach outperforms the state-of-the-art methods based on statistical analysis and syntactic analysis.

Type

a