Asad B. Sayeed

Learn More
Automatic knowledge base population from text is an important technology for a broad range of approaches to learning by reading. Effective automated knowledge base population depends critically upon coreference resolution of entities across sources. Use of a wide range of features, both those that capture evidence for entity merging and those that argue(More)
Grammatical structures for word-level sentiment detection. Title = {Grammatical structures for word-level sentiment detection}, } Links: • Data [ Abstract Existing work in fine-grained sentiment analysis focuses on sentences and phrases but ignores the contribution of individual words and their grammatical connections. This is because of a lack of both (1)(More)
How do Information Technology (IT) innovation concepts emerge, coexist, evolve, and relate to each other? To address this question, we theorize that innovation concepts are interrelated in an idea network, where they can be likened to species in a competitive and symbiotic resource space. Communities of organizations and people interested in the innovations(More)
We present an end-to-end pipeline including a user interface for the production of word-level annotations for an opinion-mining task in the information technology (IT) domain. Our pre-annotation pipeline selects candidate sentences for annotation using results from a small amount of trained annotation to bias the random selection over a large corpus. Our(More)
We investigate the effect of linguistic complexity on cogni-tive load in a dual-task scenario, namely simultaneous driving and language use. To this end, we designed an experiment where participants use a driving simulator while listening to spoken stimuli and answering comprehension questions. On-line physiological measures of cognitive load, including the(More)
Named entity recognition systems sometimes have difficulty when applied to data from domains that do not closely match the training data. We first use a simple rule-based technique for domain adaptation. Data for robust validation of the technique is then generated, and we use crowdsourcing techniques to show that this strategy produces reliable results(More)
Most recent unsupervised methods in vector space semantics for assessing thematic fit (e.g. create prototypical role-fillers without performing word sense disam-biguation. This leads to a kind of sparsity problem: candidate role-fillers for different senses of the verb end up being measured by the same " yardstick " , the single prototypical role-filler. In(More)
Due to increased competition in the IT Services business, improving quality, reducing costs and shortening schedules has become extremely important. A key strategy being adopted for achieving these goals is the use of an asset-based approach to service delivery, where standard reusable components developed by domain experts are minimally modified for each(More)
We present results of a novel experiment to investigate speech production in conversational data that links speech rate to information density. We provide the first evidence for an association between syntactic surprisal and word duration in recorded speech. Using the AMI corpus which contains transcriptions of focus group meetings with precise word(More)
We present a technique for identifying the sources and targets of opinions without actually identifying the opinions themselves. We are able to use an information extraction approach that treats opinion mining as relation mining; we identify instances of a binary " expresses-an-opinion-about " relation. We find that we can classify source-target pairs as(More)