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Handling Different Request Types
In this doc we discuss about handling different request types. We may need to handle some requests in a special way.
Requestors may ask a simple question about something. It's almost like a Google search. These are general questions and come under General request category. Until we read the request text/description, we may not be able to figure out the question.
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Where to find a good rental unit in a city? This requestor moved or planning on moving to a new city and this requestor wants to find a nice rental home in a safe neighborhood there. Requestor may type all the details in the request text. We do NOT have request specific fields YET. So, we may to find the city and/or the location where this requestor is interested in and then find volunteers in that city to help this requestor. We could categorize this type of request as a Rental type and try to find a volunteer who is a realtor by profession. If the requestor does NOT select the request category as Rental, then it would become a General query.
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Which elementary/high school is the best school for my kids?
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Where can I find an item that is specific to my country/culture in a specific city?
Some ideas to handle general type of queries: ** Shall we collect more information using some more additional fields? This information might be useful in finding the volunteers. ** Shall we use Generative AI micro service to generate some Named Entities from the request text that can be used in our search for volunteers?
Below information required from job seeker -
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Upload Resume
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Job Preferences:
- Desired Job Title/Position
- Preferred Job Location (Remote, Specific City)
- Preferred Job Type (Full-time, Part-time, Internship, Freelance)
- Expected Salary Range
- Willingness to Relocate (Yes/No)
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Skills & Experience:
- Technical Skills
- Relevant Industry Experience (total experience)
- Education Level (Grad, Undergrad)
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Availability:
- Available Start Date
- Available Work Hours (Full-time/Part-time)
Below information required from hiring manager -
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Job Information:
- Job Title/Position
- Job Description (Responsibilities, Required Skills)
- Job Location (Remote, Specific City, etc.)
- Job Type (Full-time, Part-time, Internship, Freelance)
- Salary Range Offered
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Candidate Requirements:
- Required Skills
- Required Years of Experience
- Preferred Education Level
- Certifications (if applicable)
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Workplace Preferences:
- Remote/In-person/Hybrid
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Hiring Timelines:
- Urgency of Hiring (Immediate/Specific date)
For each job seeker and hiring manager request, the algorithm will calculate a priority score based on:
Skills Matching - Compare job seeker's skills with the required skills for the job. High priority is given to how closely the job seeker’s skills match the job requirements.
Experience Matching - Match job seeker's years of experience and relevant industry experience with the hiring manager’s expectations.
Job Type - Ensure job type (e.g., full-time, part-time) match.
Salary Expectations - Ensure job seeker’s expected salary range aligns with the salary offered by the hiring manager.
Additional Preferences - Consider start date, willingness to relocate in the matching process.
The algorithm will return the top N matches ranked by the highest matching score.
Below information required from user who is looking to rent/lease -
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What location are you looking for? Specific city, neighborhood
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What is your budget for rent? Maximum price, willingness to negotiate.
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What type of housing are you looking for? Apartment, house, shared housing, etc.
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How many bedrooms and bathrooms do you need? Preferences for size or type of housing.
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Do you have any special requirements? Pet-friendly, parking space, accessibility, furnished/unfurnished.
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What is your preferred move-in date and rental duration? Short-term/long-term, immediate move-in, or future date.
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How many people will be living with you? Family size, roommates, children, etc.
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Are you looking for any amenities? Gym, pool, laundry, security, etc.
Below information required from a person who is offering a place for rent/lease-
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What is the location of the property? City, neighborhood, or proximity to notable landmarks.
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What is the rent or price you're offering? Monthly rent or total selling price, and whether it's negotiable.
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What type of housing are you offering? Apartment, house, shared housing, etc.
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How many bedrooms and bathrooms does the property have? Include additional details like size or layout if needed.
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Is the property furnished or unfurnished?
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What amenities does the property offer? Gym, pool, parking, security, etc.
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Are there any special requirements for tenants? Pet restrictions, smoking policy, minimum income requirements.
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When is the property available for move-in? Immediate or a future date.
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What is the duration of the lease? Short-term or long-term lease options.
For each housing seeker and property offerer request, the algorithm will calculate a priority score based on:
Location Matching - Compare the seeker's preferred location with the property’s location. High priority is given to proximity and neighborhood match.
Budget Matching - Ensure the seeker’s budget aligns with the rent/price offered. Closer budget matches receive higher priority.
Housing Type - Match the type of housing (apartment, house, shared) between the seeker and offerer.
Size - Match the number of bedrooms, bathrooms
Move-in Date and Lease Duration - Ensure the property's availability aligns with the seeker’s preferred move-in date and lease term.
Additional Requirements - Check for special requirements like pet-friendly or furnished housing.
The algorithm will return the top N matches ranked by the highest overall matching score.