#!/usr/bin/python
import sys import operator from decimal import *
def get_top_most_frequent_ngrams(n_grams, f): """ Get the top f most frequent n-grams """ sorted_n_grams = sorted(n_grams.items(), key=operator.itemgetter(1)) sorted_n_grams.reverse() return sorted_n_grams[0:f - 1]
def extract_character_n_grams(doctext, n): """ Parse a document text and get all the character n-grams along with their frequencies as a dictionary """ n_gram_dict = {}
i = 0 while (i + n) < len(doctext): n_gram = doctext[i:n + i] n_gram = n_gram.replace(' ', '_') n_gram = n_gram.replace('\n', '__') # print(n_gram) if n_gram in n_gram_dict:
…show more content…
Input: author_text_file - input filename of author n - length of n-grams f - count of top most frequent n-grams data_dir - folder containing sample text files of both authors Return: 'A' if input text is evaluated to be from author 'A' 'B' if input text is evaluated to be from author 'B' """ author_text = load_document_text(data_dir + '/' + author_text_file) author_n_grams = extract_word_n_grams(author_text, n)
A_author_file_scores = [] B_author_file_scores = []
print("") print("------------- Intermediate Results -------------") # evaluate
25. Identify the authors of the books Becca Nelson ordered. Perform the search using the
I just have a quick question regarding the assignment. The instructions for the assignment listed "event" as one of the options, which is why I chose when Florida was acquired and became part of the US. In your comment you stated this was too broad. Should it be more specific, such as the battle in Pensacola?
As I move forward in my education, I have become more nervous and uncertain. When I started on this journey, I thought I would make a great therapist, now that I have almost completed my coursework, uncertainty and fear have taken over any confidence I once had. In our reading Comier described a professional identity, I believe this is one of my challenges (2014). This is my third career. I spent 14 years working in laboratories doing bioscience research, another 10 years in the business side of science. In both roles, I was eager to wear the clothes and learn the behaviors that are needed to be successful. This endeavor is completely different. Although there were lives involved with the bioscience job, I could only do what the biology would let me do. I never felt like anything was my fault, if things went wrong we had a team of people try and figure it out. In business, who cares if we didn’t make the deal or the project fell apart. This challenge is about people, their lives and giving them hope and tools to help make their life journey fit closer to what they want it to be. That is very intimidating. I realize I have some natural skills that help me build congruency fairly quickly, but I have no idea how to use that skill. I have read and studied and done enrichment in addition to my schoolwork and I do not feel prepared to talk with clients. So I would measure my current competency as
Case Conceptualization A young female named Jane was concerned about her worsening condition of anxiety due to the fact that it coincided with her depression and she felt she was in a vicious cycle. She made inquiries and read from one of the originators and creator’s books. The treatment which the author explained she felt would be relatable and the passage that persuaded Jane to look further in to this approach was ”Rogers theory of development posits that conditional love leads to a distorted experience, which fostes an incongruent self –concept. Incongruence makes one prone to recurrent anxiety, which triggers defensive behavior, which fuels more incongruence ”
I made two lists on two different pages on blank printer paper. On the Trigram and Word condition list is written ten random letters that are centered and descend equally spaced down the page. I have decided to use the same order of the lists for each participant, which is the Trigram condition list followed by the Word condition list. The guidelines given to the participants for this experiment were easy. Each of the participants were first asked to look at the Trigram condition word list for thirty seconds. Then the participants
| a. Entire Book * When a book has multiple authors you are supposed to list them in alphabetical order. 1. Author, A.A. (1967). Title of Work. Location: Publisher. 2. Author, A.A. (1997). Title of Work. Retrieved from http://www.xxxxx 3. Author, A.A. (2006). Title of Work. doi:xxxxx 4. Editor, A.A. (Ed.).(1986) Title of work. Location: Publisher. b. Chapter in a Book 5. Author, A.A., & Author B.B. (1995). Titlte of chapter entry. In A. Editor, B. Editor & C. Editor (Eds.) Title of Book (pp. xxx-xxx). Location: Publisher.
the case that there is more than one author out then in alphabetical order. It is important to do
In order to examine the difference on the average number of words between the two groups and among 13 compositions, I conducted two-way ANOVA. The result shows that groups has statistically significant. But words are not statistically significant difference. Words X Groups are also no statistically significant difference.
The participants were told they would be shown a screen of words, and were told that after viewing the words they should form an impression of a hypothetical person and will have to answer an online questionnaire which according to the hypothesis should help us gain results which will contribute to research towards primacy effect. The participants were shown their respective trait lists, depending on the group they were assigned to. Each word was shown for 3 seconds with an interval of 1.5 seconds between trait adjectives, after being shown the words the participants were asked to complete an online questionnaire which consisted of 6 questions. To test the hypothesis, we must calculate the mean score and standard deviation for
Many digital libraries (such as: Google Scholar, PubMed, CiteSeer etc..) exist which help in retrieving the scholarly research publications. The only unique key to search in these libraries is the author name. The problem of ambiguity in name creates difficulty in identifying the publications of the same author. This author name ambiguity in research publications occur due to multiple authors having identical names (Polysem) or same author having multiple names (Synonym). This type of ambiguity problem is serious and effects the performance of a search engine while retrieving publications based on author names.
• Chi square: In our proposed system we utilized chi square as a scoring capacity with which we can discover if two terms are related to each other We at that point apply chi square capacity which gives the scoring capacity. Subsequent to applying chi square we learn whether the bigram or trigram happens as much of the time as every individual word.
∑A(di, ti) = 1, where i=1 to m. In PLSI, each term ti in document di is originated from a latent semantic variable class, zl (l = 1, 2, …, k), that implies the conditional independence of ti and di, on the state of the associated latent topic variable. The joint probability of di and ti is calculated as follows:
Figure 1 is a line graph that shows the correlation between the frequency (y) and the rank (x) of the top 100 most frequent words in the pre-mentioned academic corpus. As in Zipf’s Law, the frequency of a word in a corpus of natural language is inversely proportional to its rank in the frequency table. That is, the most frequent word occurs approximately twice as often as the second most frequent word, three times as often as the third most frequent word, etc.
Assume n be the total number of documents in the collection, pi(w) be the conditional probability of class i for documents which contain w, Pi be the global fraction of documents containing the class i, and F(w) be the global fraction of documents which contain the word w. Then, the x2-statistic of the word between word w and class i is defined[1]
Another study by (Ben Verhoeven &WalterDaelemans, in 2014) designed to serve multiple purposes: disclosure of age, gender, authorship, personality, feelings, deception, subject and gender. Another major feature is the planned annual expansion with new students each year. The corpus currently has about 305,000 codes distributed on 749 documents. The average