解释查询变量的协调、复合生成和结果融合

Johannes Leveling
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引用次数: 4

摘要

我们研究了将协调(例如与“and”和“or”等协调连词相连的单词序列)解释为术语的逻辑析取,以生成一组用于信息检索(IR)查询的无析取查询变体。此外,所谓的连字符协调是通过生成完整的复合形式和改写原始查询来解决的,例如:由“大米进出口”转变为“大米进出口”。然后分别处理查询变量,并使用标准数据融合技术合并检索结果。我们对德国标准IR基准数据的方法进行了评估。结果表明:i)我们提出的从连字符配位生成复合词的方法对所有测试主题都产生了正确的结果。ii)我们提出的基于浅层自然语言处理(NLP)技术的识别协调和生成查询变体的启发式方法在主题上非常准确,并且不依赖于解析或词性标记。iii)使用查询变量产生多个检索结果并合并结果会降低顶级的精度。然而,结合盲目相关反馈(BRF),这种方法可以比使用原始查询的标准BRF基线显示出显著的改进。
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Interpretation of coordinations, compound generation, and result fusion for query variants
We investigate interpreting coordinations (e.g. word sequences connected with coordinating conjunctions such as "and" and "or") as logical disjunctions of terms to generate a set of disjunctionfree query variants for information retrieval (IR) queries. In addition, so-called hyphen coordinations are resolved by generating full compound forms and rephrasing the original query, e.g. "rice im-and export" is transformed into "rice import and export". Query variants are then processed separately and retrieval results are merged using a standard data fusion technique. We evaluate the approach on German standard IR benchmarking data. The results show that: i) Our proposed approach to generate compounds from hyphen coordinations produces the correct results for all test topics. ii) Our proposed heuristics to identify coordinations and generate query variants based on shallow natural language processing (NLP) techniques is highly accurate on the topics and does not rely on parsing or part-of-speech tagging. iii) Using query variants to produce multiple retrieval results and merging the results decreases precision at top ranks. However, in combination with blind relevance feedback (BRF), this approach can show significant improvement over the standard BRF baseline using the original queries.
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