Most Web pages contain temporal information. However, most of previous studies only consider the update time of Web pages rather than fully exploit different temporal features in Web. In this paper, we propose a novel approach to fusing different temporal features in Web pages to build an efficient index structure for temporal-textual Web search. Specially, we focus on update time and content t...

Affective analysis of images in social networks has drawn much attention, and the texts surrounding images are proven to provide valuable semantic meanings about image content, which can hardly be represented by low-level visual features. In this paper, we propose a novel approach for visual affective classification (VAC) task. This approach combines visual representations along with novel text...

A proper semantic representation of textual information underlies many natural language processing tasks. In this paper, a novel semantic annotator is presented to generate conceptual features for text documents. A comprehensive conceptual network is automatically constructed with the aid of Wikipedia which has been represented as a Markov chain. Furthermore, semantic annotator gets a fragment ...

Semantic Textual Similarity (STS) devotes to measuring the degree of equivalence in the underlying semantic of the sentence pair. We proposed a new system, ITNLPAiKF, which applies in the SemEval 2017 Task1 Semantic Textual Similarity track 5 English monolingual pairs. In our system, rich features are involved, including Ontology based, word embedding based, Corpus based, Alignment based and Li...

We evaluate several different overlay routing structures for supporting interactivity features in End Sysytem Multicast. Interactivity features include low-bandwidth textual chat, as well as higher-bandwidth audio conferencing and immersive audio applications. Overlays are evaluated using real interaction patterns seen in IRC, as well as real join and leave patterns from an ESM video broadcast....

In this paper we show the surprising effectiveness of a simple observed features model in comparison to latent feature models on two benchmark knowledge base completion datasets, FB15K and WN18. We also compare latent and observed feature models on a more challenging dataset derived from FB15K, and additionally coupled with textual mentions from a web-scale corpus. We show that the observed fea...

ABSTRACT Textual Entailment (TE) is a critical issue in natural language processing (NLP). In this paper we report our approach to the Chinese textual entailment and the system result on NTCIR-10 RITE-2 both simplified and traditional Chinese dataset. Our approach is based on more observation on training data and finding more types of linguistic features. The approach is a complement to the tra...

This paper presents the results achieved during our participation at the MediaEval 2017 Retrieving Diverse Social Images Task. The proposed unsupervised multimodal approach exploits visual and textual information in a fashion that prioritizes both relevance and diversification. As features, we used a modified version of the RMAC (Regional Maximum Activation of Convolutions) descriptor for visua...

The output of automatic speech recognition systems is generally an unpunctuated stream of words which is hard to process for both humans and machines. We present a two-stage recurrent neural network based model using long short-term memory units to restore punctuation in speech transcripts. In the first stage, textual features are learned on a large text corpus. The second stage combines textua...