NDCG
Related Papers
Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization
AbstractFast and effective automated indexing is critical for search and personalized services. Key phrases that consist of one or more words and represent the main concepts of the document are …...
Knowledge Graph and Corpus Driven Segmentation and Answer Inference for Telegraphic Entity-seeking Queries
Much recent work focuses on formal in- terpretation of natural question utterances, with the goal of executing the resulting structured queries on knowledge graphs (KGs) such as Freebase. Here we …...
Evaluating Translation Quality and CLIR Performance of Query Sessions
AbstractThis paper presents the evaluation of the translation quality and Cross-Lingual Information Retrieval (CLIR) performance when using session information as the context of queries. The hypothesis is that previous queries …...
RankDCG: Rank-Ordering Evaluation Measure
AbstractRanking is used for a wide array of problems, most notably information retrieval (search). Kendall’s τ, Average Precision, and nDCG are a few popular approaches to the evaluation of ranking. …...
Answering Legal Questions by Learning Neural Attentive Text Representation
AbstractText representation plays a vital role in retrieval-based question answering, especially in the legal domain where documents are usually long and complicated. The better the question and the legal documents …...
History for Visual Dialog: Do we really need it?
AbstractVisual Dialogue involves “understanding” the dialogue history (what has been discussed previously) and the current question (what is asked), in addition to grounding information in the image, to accurately generate …...
VD-BERT: A Unified Vision and Dialog Transformer with BERT
AbstractVisual dialog is a challenging vision-language task, where a dialog agent needs to answer a series of questions through reasoning on the image content and dialog history. Prior work has …...
Content-based Models of Quotation
AbstractWe explore the task of quotability identification, in which, given a document, we aim to identify which of its passages are the most quotable, i.e. the most likely to be …...