ISBNdun kongresua

Detection of Reading Absorption in User-Generated Book Reviews: Resources Creation and Evaluation

To detect how and when readers are experiencing engagement with a literary work, we bring together empirical literary studies and language technology via focusing on the affective state of absorption. The goal of our resource development is to enable the detection of different levels of reading absorption in millions of user-generated reviews hosted on social reading platforms. We present a corpus of social book reviews in English that we annotated with reading absorption categories.

Linguistic Appropriateness and Pedagogic Usefulness of Reading Comprehension Questions

Automatic generation of reading comprehension questions is a topic receiving growing interest in the NLP community, but there is currently no consensus on evaluation metrics and many approaches focus on linguistic quality only while ignoring the pedagogic value and appropriateness of questions. This paper overcomes such weaknesses by a new evaluation scheme where questions from the questionnaire are structured in a hierarchical way to avoid confronting human annotators with evaluation measures that do not make sense for a certain question.

Domain Adapted Distant Supervision for Pedagogically Motivated Relation Extraction

In this paper we present a relation extraction system that given a text extracts pedagogically motivated relation types, as a previousstep to obtaining a semantic representation of the text which will make possible to automatically generate questions for reading comprehension. The system maps pedagogically motivated relations with relations from ConceptNet and deploys Distant Supervisionfor relation extraction. We run a study on a subset of those relationships in order to analyse the viability of our approach.

Evaluating Multimodal Representations on Visual Semantic Textual Similarity

The combination of visual and textual representations has produced excellent results in tasks such as image captioning and visual question answering, but the inference capabilities of multimodal representations are largely untested. In the case of textual representations, inference tasks such as Textual Entailment and Semantic Textual Similarity have been often used to benchmark the quality of textual representations. The long term goal of our research is to devise multimodal representation techniques that improve current inference capabilities.


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