Global ETD Search
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Showing 1 to 5 of 5 for “"reciprocal rank"”.
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Question Answering on Dynamic Knowledge Graph for Chemistry
… question embeddings. Answer candidates are ranked based on triple likelihood calculated from the topic entity, predicted relation, and candidate embeddings. A novel Knowledge Graph embedding algorithm, TransRA, has numerically higher filtered mean reciprocal rank than other embedding …
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Community Question Answering : an Investigation into the Influence of Question Expansion based on User's Explicit Information on Learning to Rank Q&A Models
… is crucial for accurately predicting the ranked list of answer candidates. Community answer retrieval aims to answer new user questions by leveraging answers from previous users' questions. Automated Learning-to-Rank (LTR) models for Community Question Answering (CQA) require additional …
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Log-Driven Robust Anomaly Detection and Root Cause Localisation for Distributed Computing Systems
… abnormal executions at the session level, and ranking a short list of diagnostic lines within each abnormal session so that engineers can act quickly. The first contribution is a session level detector that combines a deterministic task splitting policy with a two layer LSTM over event …
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Active evaluation of predictive models
… the objective of an evaluation could be to rank the models according to the risk that they incur or to identify the model with lowest risk. An experimental study shows that the active procedure leads to higher test power than the standard test in many application domains. Finally, we study …
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Recomendr-entity recommendation based on ad-hoc dimensions
The growing availability and popularity of opinion rich resources on the online web resources, such as review sites and personal blogs, has made it convenient to find out about the opinions and experiences of layman people. But, simultaneously, this huge eruption of data has made it difficult to …