A growing number of applications, e.g. video surveillance and medical image analysis, require training recognition systems from large amounts of weakly annotated data while some targeted interactions with a domain expert are allowed to improve the training process. In such cases, active learning (AL) can reduce labeling costs for training a classifier by querying the expert to provide the label...

The information obtained from the Web is increasingly important for decision making and for our everyday tasks. Due to the growth of uncertified sources, blogosphere, comments in the social media and automatically generated texts, the need to measure the quality of text information found on the Internet is becoming of crucial importance. It has been suggested that factual density can be used to...

This paper investigates how a pair of signals about the type of the agent can be compared in the classical principal agent model with adverse selection. Signal comparison in this model has two distinctive features that make it di cult to directly apply the results from decision theory: timing of the game and the number of incentive compatibility constraint. The signal in the model takes the for...

Speech categories are defined by multiple acoustic dimensions, and listeners give differential weighting to dimensions in phonetic categorization. The informativeness (predictive strength) of dimensions for categorization is considered an important factor in determining perceptual weighting. However, it is unknown how the perceptual system weighs acoustic dimensions with similar informativeness...

The information overload faced by today’s society poses great challenges to researchers who want to find a relevant piece of information. Automatic summarisation is a field of computational linguistics which can help humans to deal with this information overload by automatically extracting the gist of documents. This thesis attempts to gain insights into the automatic summarisation field from s...

Using the staggered adoption of universal demand (UD) laws in United States, we show that reduction shareholder litigation risk deteriorates firms’ stock price informativeness. This informativeness is due to firms changing way they invest rather than obfuscating or withholding firm-specific information. We also associated with higher investment-price sensitivity. Overall, despite causing a dete...

This study was conducted to determine the influence of Shopee's Viral Marketing in TikTok on consumers’ attitude at Shopee. The purpose this is explain how informativeness, entertainment, irritation, credibility viral marketing video and their attitudes video. uses quantitative methods with descriptive - causal purposes. Non-probability sampling has been used type purposive sampling. number res...

We study the information aggregation process in a laboratory financial market where traders have access to costly private and free public imperfect information. The disclosure provokes (i) crowding-out effect on traders’ demand, (ii) overreaction signal, (iii) deterioration price informativeness. show that reduction informativeness is direct consequence of overweighting when aggregated prices. ...

This study draws on prior research on corporate governance and examines whether the informativeness of earnings, proxied by the earnings±returns relationship, varies with the fraction of outside directors serving on the board and board size. The results suggest that earnings of ®rms with the smallest boards in the sample (with a minimum of ®ve board members) are perceived as being more informat...

Open Information Extraction (OIE) systems extract relational tuples from text without requiring to specify in advance the relations of interest. Systems perform well on widely used metrics such as precision and yield, but a close look at systems output shows a general lack of informativeness in facts deemed correct. We propose a new evaluation protocol, based on question answering, that is clos...