# Machine Learning Based Recommendation System for Web-Search Learning
## 3 Materials and Methods
### Architecture of the Proposed Model  
The architecture of the proposed model to analyze and track online resource usage is sketched in Figure 1 with the core operations--information logging, information processing, and word mapping [7; 8; 9; 10; 11; 12; 13; 14; 34; 35; 36; 37; 38]. The proposed model of resource processing is defined in Algorithm 1. ```
1:Data or information logging
1.1 Evaluate prior knowledge. 1.2 Perform online search learning. 1.3 Map online resources into log files and transcript information. 1.4 Evaluate the post-knowledge. 2:Processing the data or information. 2.1 Extract the words using the concept assessment. 2.2 Use the software to recognize the text, image, and video resources. 2.3 Extract the words using the post-knowledge assessment. 3: Define the mapping operation. 3.1 Remove the unnecessary words after preprocessing. 3.2 Perform the word match between video and webpages information. 3.3 Construct the word origin table with the resources. ```  
**Algorithm 1**Proposed Model--Resources Processing  
The proposed model differs from the existing models by recording the complete log files, eye-tracking information, and the history of the visited resources, including date and time. This feature dramatically helps to map the knowledge that has been recently learned to the available resources. This information is read and processed through the proposed model to generate each learner's complete history of phrases or words. The video transcripts help to trace the phrases searched in the videos. The overlapping between words is analyzed using the proposed resources processing model. The proposed resources processing model is analyzed in several dimensions to answer the following queries:  
Q1. How many web pages are visited by the learners? That is, during the online search learning session, the learners access to different web pages should be analyzed, for example, the access to YouTube, Google search, and other searches from various search engines. Q2. How many images are seen by the learners? The sequences of images searched from the different search engines to the learner's topics of interest in updating their knowledge should be analyzed for the period. Q3. How many videos are accessed by the learners? The searched and watched videos based on the learning topics and subtopics through several search engines should be analyzed. Q4. Which of the web pages are visited most by the learners? In this case, the primary interest of analysis is in searching and accessing the specific or the most frequently accessed webpage information for all learners. Q5. How are the complete eye track and log file information stored for all learners? To analyze the acquired knowledge of the learners during the simulation, the complete history of the eye tracker and the search should be saved in the system over the simulated period. Q6. How do we find the mapping between the information that has been newly learned to resource processing?The transcripts are generated for the accessed videos, and the searched words of the learners are extracted during the simulation to construct the retrace of word origins corresponding to the available information resources. Q7. How do we identify the sequence of words the learners had learned online? Based on the search history, the comparison should be performed by generating the list of original words and retracing the words to specific information resources. Q8. How to keep track of the words encountered through online videos? The learners are asked to write a detailed report about the learning topics before and after completing the learning phase to analyze the words encountered through the videos. Q9. How to analyze the overlapping between the traversed words and the recalled data? The information about the learning topics is analyzed based on the number of written phrases and the concepts learned. Q10. How do we analyze the outcomes for learners who learned a particular topic through web searching?