Titlebook: Web Information Systems Engineering – WISE 2016; 17th International C Wojciech Cellary,Mohamed F. Mokbel,Yanchun Zhang Conference proceedin

ENNUI

Urea508

Improving Object and Event Monitoring on Twitter Through Lexical Analysis and User Profilingrvations and their implicitly associated time and location data are a valuable source of information for monitoring objects and events, such as earthquake, hailstorm, and shooting incidents. However, given the informal and uncertain expressions used in personal Twitter messages, and the various type

adjacent

Aspect-Based Sentiment Analysis Using Lexico-Semantic Patterns content is written, however, prevents straightforward analysis. Instead, natural language processing techniques are required to quantify the textual information embedded within text. This research focuses on extracting the sentiment that can be found in consumer reviews. In particular, we focus on

ZEST

arcane

Multilevel Browsing of Folksonomy-Based Digital Collections to which it is possible to incrementally narrow down the set of selected objects in a collection by sequentially adding more and more filtering tags. For this purpose, we present a browsing strategy based on finite automata. As well, we provide some experimental results concerning the application o

mydriatic

附录

essential-fats

Jogging

增减字母法

Personalized Re-ranking of Tweetsin chronological order and have to scan through pages of tweets to find useful information. In this paper, we propose a personalized tweet re-ranking framework for re-ranking the tweets received by a user based on his preference such that interesting tweets are ranked higher for the user. With the p