Improved query difficulty prediction for the web

Hauff, Claudia; Murdock, Vanessa; Baeza-Yates, Ricardo

doi:10.1145/1458082.1458142

Cited by 68 publications

(57 citation statements)

References 16 publications

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“…Seven of these predictors were pre-retrieval predictors and these were : Average Pointwise Mutual Information (AvPMI) [10], Simplified Clarity Score (SCS) [11], Average Inverse Collection Term Frequency (AvICTF) [12], Average Inverse Document Frequency (AvIDF) [10] and the derivatives of the similarity score between collection and query (SumSCQ, AvSCQ, MaxSCQ) [27]. One post-retrieval predictor was used, the Clarity Score (CS) [5].…”

Section: Creating Training and Testing Instances For Missing Content mentioning

confidence: 99%

Detecting Missing Content Queries in an SMS-Based HIV/AIDS FAQ Retrieval System

Thuma

Rogers

Ounis

2014

Lecture Notes in Computer Science

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Abstract. Automated Frequently Asked Question (FAQ) answering systems use pre-stored sets of question-answer pairs as an information source to answer natural language questions posed by the users. The main problem with this kind of information source is that there is no guarantee that there will be a relevant question-answer pair for all user queries. In this paper, we propose to deploy a binary classifier in an existing SMS-Based HIV/AIDS FAQ Retrieval System to detect user queries that do not have the relevant question-answer pair in the FAQ document collection. Before deploying such a classifier, we first evaluate different feature sets for training in order to determine the sets of features that can build a model that yields the best classification accuracy. We carry out our evaluation using seven different feature sets generated from a query log before and after retrieval by the FAQ retrieval system. Our results suggest that, combining different feature sets markedly improves the classification accuracy.

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Section: Creating Training and Testing Instances For Missing Content mentioning

confidence: 99%

Detecting Missing Content Queries in an SMS-Based HIV/AIDS FAQ Retrieval System

Thuma

Rogers

Ounis

2014

Lecture Notes in Computer Science

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“…Topical drift can be controlled by appropriate query performance prediction applied to decide whether a query should be expanded and how [4]. In particular, our work is related to methods for post-retrieval query prediction, i.e., methods that use results lists returned by an initial retrieval run as the basis for their performance prediction.…”

Section: Query Performance Predictionmentioning

confidence: 99%

“…The datasets are referred to as DS-1 and DS-2 and correspond to the MediaEval 2010 development and test dataset, respectively. Both datasets consist of the news magazine, science news, news reports, documentaries, educational programming and archival videos, provided by The Netherlands Institute for Sound and Vision (S&V) 4 . For the experiments, we use both DS-1 and DS-2 to investigate generalization of our approach across datasets.…”

Section: Datasetsmentioning

confidence: 99%

Leveraging visual concepts and query performance prediction for semantic-theme-based video retrieval

Rudinac

Larson

Hanjalic

2012

Int J Multimed Info Retr

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In this paper, we present a novel approach that utilizes noisy shot-level visual concept detection to improve text-based video retrieval. As opposed to most of the related work in the field, we consider entire videos as the retrieval units and focus on queries that address a general subject matter (semantic theme) of a video. Retrieval is performed using a coherence-based query performance prediction framework. In this framework, we make use of video representations derived from the visual concepts detected in videos to select the best possible search result given the query, video collection, available search mechanisms and the resources for query modification. In addition to investigating the potential of this approach to outperform typical text-based video retrieval baselines, we also explore the possibility to achieve further improvement in retrieval performance through combining our concept-based query performance indicators with the indicators utilizing the spoken content of the videos. The proposed retrieval approach is data driven, requires no prior training and relies exclusively on the analyses of the video collection and different results lists returned for the given query text. The experiments are performed on the Media Eval 2010 datasets and demonstrate the effectiveness of our approach.

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“…There, topicbased video search was performed by combining the query-performance prediction (QPP) principle (e.g. [10] [77] [27]) with the results of many visual concept detectors aggregated across a video into a meta-level video representation. This representation is deployed by a QPP framework to evaluate the coherence (e.g.…”

Section: Advanced Semantic Inference: Inferring the Aboutness Of The mentioning

confidence: 99%

New grand challenge for multimedia information retrieval: bridging the utility gap

Hanjalic

2012

Int J Multimed Info Retr

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This is the author-created version of the article. The final publication is available at www.springerlink.com.Abstract The needs and expectations regarding multimedia content access have grown rapidly with the fast development of multimedia technology and the explosion of multimedia content around us. This imposed high demands on the level of sophistication of multimedia information retrieval (MIR) solutions. Although the potential to develop the MIR technology that meets such high demands has also rapidly grown over the years, we are not there yet with adequate solutions. This paper states that a significant step forward could become possible if the MIR field moves towards a utilitycentered research focus. There, the criteria related to utility should be deployed to help us bridge the critical remaining gap that is in front of us -the utility gap, the gap between the expected and de facto usefuleness of MIR systems. Utility criteria reach beyond the objective relevance of MIR results to also consider their informativeness and how helpful they are for user's further actions. Bridging the utility gap can therefore be seen as the next grand challenge in the MIR research field. To pursue this challenge, we propose a utility-by-design approach, by which utility is targeted explicitly and embedded deep in the foundations of MIR solutions. The paper will first motivate this new MIR grand challenge and position it in respect to the current efforts in the field. Then, some possibilities for realizing the utilityby-design approach will be highlighted and translated into a number of recommended research directions.

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Improved query difficulty prediction for the web

Cited by 68 publications

References 16 publications

Detecting Missing Content Queries in an SMS-Based HIV/AIDS FAQ Retrieval System

Detecting Missing Content Queries in an SMS-Based HIV/AIDS FAQ Retrieval System

Leveraging visual concepts and query performance prediction for semantic-theme-based video retrieval

New grand challenge for multimedia information retrieval: bridging the utility gap

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