Task Feasibility Sample Clauses

Task Feasibility. ‌ The task of automatic personality prediction on monologue text dataset has shown to be a feasible task by previous studies. However, nobody has shown that this task is also feasible on dialogue text corpus. In order to evaluate the feasibility of the task, we will develop the state- of-art models and see how the models perform on our new corpus. It will not be surprising if the models perform worse on the dialogue corpus because our corpus is more challenging than previous dialogue datasets and even human beings show little consensus. If the state-of-art models are not successful on the new corpus, we should start designing new models to adapt to the different structure of dialogue data. After extracting LIWC features using ▇▇▇▇▇▇▇▇▇▇’▇ LIWC tool, we feed the dataset into Weka to build the two best-performing classification models (SMO, and simpleLogistic) men- tioned in the paper [1] without any feature reduction. Table 5.1: Comparison between LIWC features and word embeddings. Multilayer Perceptron, the baseline neural network, is in both cases. FastText is used to train our word embeddings on Friends and other large-scale datasts. 5.1.1 LIWC vs word embeddings‌ The large number of misspellings in both datasets pose a serious challenge to the appli- cation of pre-trained word vectors because they are unlikely to appear in the pre-trained word embeddings [2]. However, this problem can be solved by utilizing a character-level word embed- dings because it is able to compose similar word embeddings for those misspelled or irregular words as their corresponding standard spelling. Specifically, we use fastText [36] n-character embeddings trained on a dataset which combines New York Times corpus, the Wikipedia text dump, the Amazon Book Reviews, and the transcripts from several TV shows including Friends in our paper. To see whether word embeddings also contain the linguistic cues necessary to the task of automatic personality prediction, we design a small experiment on the essays dataset. Specif- ically, we feed the essays dataset into the same MLP model using LIWC features and word embeddings respectively. The results (Table 5.1) below demonstrate that the same model has a better accuracy in 3 out of 5 personality traits on the same dataset. As a result, we are able to confirm that word embeddings are effective linguistic features for automatic personality prediction. In the following experiments, we can keep using pre-trained word vectors for our task. 5.1....
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  • Feasibility Each of the Project Budget, the Project Schedule and the Disbursement Schedule is realistic and feasible.

  • Technical Feasibility of String While ICANN has encouraged and will continue to encourage universal acceptance of all top-­‐level domain strings across the Internet, certain top-­‐level domain strings may encounter difficulty in acceptance by ISPs and webhosters and/or validation by web applications. Registry Operator shall be responsible for ensuring to its satisfaction the technical feasibility of the TLD string prior to entering into this Agreement.

  • Feasibility Study Buyer is granted the right to conduct engineering and/or market and economic feasibility studies of the Property and a physical inspection of the Property, including studies or inspections to determine the existence of any environmental hazards or conditions (collectively, the “Feasibility Study”) during the period (the “Feasibility Period”) commencing on the Effective Date and ending at 5:00 p.m., Central Time, on the June 3, 2010. With Seller’s permission, after Seller has received advance notice sufficient to permit it to schedule in an orderly manner Buyer’s examination of the Property and to provide at least 24-hours’ advance written notice to any affected tenants, Buyer or its designated agents may enter upon the Property during normal business hours for purposes of analysis or other tests and inspections which may be deemed necessary by Buyer for the Feasibility Study. Buyer or its designated representative must be accompanied by a designated representative of Seller or have received Seller’s written permission prior to entering upon the Property in connection with Buyer’s Feasibility Study; provided, however, Buyer may not enter into any space leased by any tenant without being accompanied by a designated representative of Seller. Seller agrees to make its representative reasonably available during normal business hours. Buyer will not alter the physical condition of the Property or conduct invasive testing without notifying Seller of its requested tests, and obtaining the written consent of Seller to any physical alteration of the Property or invasive testing. Buyer will utilize commercially reasonable diligence to conduct or cause to be conducted all inspections and tests in a manner and at times which will not unreasonably interfere with any tenant’s use and occupancy of the Property. If Buyer determines, in its sole judgment, that the Property is not suitable for any reason for Buyer’s intended use or purpose, or is not in satisfactory condition, then Buyer may terminate this Contract by written notice to Seller prior to expiration of the Feasibility Period, in which case the ▇▇▇▇▇▇▇ Money (other than the Option Money) will be returned to Buyer, and neither party shall have any further right or obligation hereunder other than as set forth herein with respect to rights or obligations which survive termination. If this Contract is not terminated pursuant to this Section 5(a), then after expiration of the Feasibility Period, after Seller has received advance notice sufficient to permit it to schedule in an orderly manner Buyer’s examination of the Property and to provide at least 24-hours’ advance written notice to any affected tenants, Buyer or its designated agents may enter upon the Property during normal business hours. Buyer or its designated representative must be accompanied by a designated representative of Seller or have received Seller’s written permission prior to entering upon the Property; provided, however, Buyer may not enter into any space leased by any tenant without being accompanied by a designated representative of Seller. If this Contract is not timely terminated pursuant to this Section 5(a), Buyer’s right to terminate this Contract pursuant to this Section 5(a) and any and all objections with respect to the Feasibility Study will be deemed to have been waived by Buyer for all purposes.

  • Development Reports Beginning six months after Effective Date and ending on the date of first commercial sale of a Licensed Product in the United States, LICENSEE shall report to Cornell progress covering LICENSEE's (and Affiliate's and Sublicensee's) activities and efforts in the development of rights granted to LICENSEE under this Agreement for the preceding six months. The report shall include, but not be limited to, activities and efforts to develop and test all Licensed Products and obtain governmental approvals necessary for marketing the same. Such semi-annual reports shall be due within sixty days (60) of the reporting period and shall use the form as provided herein as Appendix C.

  • Research Use Reporting To assure adherence to NIH GDS Policy, the PI agrees to provide annual Progress Updates as part of the annual Project Renewal or Project Close-out processes, prior to the expiration of the one (1) year data access period. The PI who is seeking Renewal or Close-out of a project agree to complete the appropriate online forms and provide specific information such as how the data have been used, including publications or presentations that resulted from the use of the requested dataset(s), a summary of any plans for future research use (if the PI is seeking renewal), any violations of the terms of access described within this Agreement and the implemented remediation, and information on any downstream intellectual property generated from the data. The PI also may include general comments regarding suggestions for improving the data access process in general. Information provided in the progress updates helps NIH evaluate program activities and may be considered by the NIH GDS governance committees as part of NIH’s effort to provide ongoing stewardship of data sharing activities subject to the NIH GDS Policy.