We propose multi-modal story-oriented video summarization (MMSS) which, unlike previous works that use fine-tuned, domain-specific heuristics, provides a domain-independent, graph-based framework. MMSS uncovers correlations between information of different modalities and gives meaningful story-oriented news video summaries. MMSS can also be applied for video retrieval, achieving performance tha...

In our second participation to the DUC evaluation, we used the SumUM system for the multidocument summarization focused by events task and summaries in response to a question task. Our multi-document summarization algorithm is based on the use of background information gathered by summarizing previous texts, which is then combined with a new document of the cluster. For producing the summaries ...

This paper describes Peking University’s approach to the Ad Hoc Track. In our first participation, results for all four tasks were submitted: the Best In Context, the Focused, the Relevance In Context and the Thorough. Based on retrieval method Okapi BM25, we implement two different ranking methods NormalBM25 and LearningBM25 according to different parameter settings. Specially, the parameters ...

This paper describes the methods we used for the Ad Hoc task of TREC Genomics Track. Synonym dictionary for genes and pseudo relevance feedback are used to expand queries. BM25 model is implemented to retrieve relevant documents. We also tried to exploit name entities and their co-references in the retrieval. Results of submitted runs are listed and discussed.

An approach to find the most probable English source document for the given Hindi suspicious document is presented. The approach does not involve any complex method of Machine Translation (MT) as a language normalization pre-processing step, rather it relies on standard cross-language resources available between Hindi-English and calculates the similarity using the Okapi BM25 model. We also pre...

This paper presents an evaluation and an analysis of some selected information retrieval models for Bengali monolingual information retrieval task. Two models, TF-IDF model and the Okapi BM25 model have been considered for our study. The developed IR models are tested on FIRE ad hoc retrieval data sets released for different years from 2008 to 2012 and the obtained results have been reported in...

The effectiveness of BM25 retrieval function is mainly due to its sub-linear term frequency (TF) normalization component, which is controlled by a parameter k1. Although BM25 was derived based on the classic probabilistic retrieval model, it has been so far unclear how to interpret its parameter k1 probabilistically, making it hard to optimize the setting of this parameter. In this paper, we pr...

We describe DCU’s participation in the NTCIR-11 SpokenQuery&Document task. We participated in the spokenquery spoken content retrieval (SQ-SCR) subtask by using the slide group segments as basic indexing and retrieval units. Our approach integrates normalised prosodic features into a standard BM25 weighting function to increase weights for terms that are prominent in speech. Text queries and re...